Adaptive motion tracking for fast block motion estimation. - Jian Feng 006; Tie-Yan Liu; Kwok-Tung Lo; Xu-Dong Zhang 001 (ISCAS (5), 2001)

Constant false-alarm ratio processing for video cut detection. - Tie-Yan Liu; Xudong Zhang 001; Linwei Shan; Yingning Peng (ICIP (1), 2002)

Dynamic selection and effective compression of key frames for video abstraction. - Xu-Dong Zhang 001; Tie-Yan Liu; Kwok-Tung Lo; Jian Feng 006 (Pattern Recognit. Lett., 2003)

Frame interpolation scheme using inertia motion prediction. - Tie-Yan Liu; Kwok-Tung Lo; Jian Feng 006; Xudong Zhang 001 (Signal Process. Image Commun., 2003)

Time-constraint boost for tv commercials detection. - Tie-Yan Liu; Tao Qin 001; HongJiang Zhang (ICIP, 2004)

A Linear Approximation Based Method for Noise-Robust and Illumination-Invariant Image Change Detection. - Bin Gao 001; Tie-Yan Liu; QianSheng Cheng; Wei-Ying Ma (PCM (3), 2004)

Microsoft Research Asia at Web Track and Terabyte Track of TREC 2004. - Ruihua Song; Ji-Rong Wen; Shuming Shi 001; Guomao Xin; Tie-Yan Liu; Tao Qin 001; Xin Zheng; Jiyu Zhang; Gui-Rong Xue; Wei-Ying Ma (TREC, 2004)

A new cut detection algorithm with constant false-alarm ratio for video segmentation. - Tie-Yan Liu; Kwok-Tung Lo; Xu-Dong Zhang 001; Jian Feng 006 (J. Vis. Commun. Image Represent., 2004)

Shot reconstruction degree: a novel criterion for key frame selection. - Tie-Yan Liu; Xudong Zhang 001; Jian Feng 006; Kwok-Tung Lo (Pattern Recognit. Lett., 2004)

Subsite Retrieval: A Novel Concept for Topic Distillation. - Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; Guang Feng; Wei-Ying Ma (AIRS, 2005)

Calculating Webpage Importance with Site Structure Constraints. - Hui-Min Yan; Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; Guang Feng; Wei-Ying Ma (AIRS, 2005)

Level-Based Link Analysis. - Guang Feng; Tie-Yan Liu; Xu-Dong Zhang 001; Tao Qin 001; Bin Gao 001; Wei-Ying Ma (APWeb, 2005)

Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering. - Bin Gao 001; Tie-Yan Liu; Xin Zheng; QianSheng Cheng; Wei-Ying Ma (KDD, 2005)

Similarity space projection for web image search and annotation. - Ying Liu 026; Tao Qin 001; Tie-Yan Liu; Lei Zhang 001; Wei-Ying Ma (Multimedia Information Retrieval, 2005)

Web image clustering by consistent utilization of visual features and surrounding texts. - Bin Gao 001; Tie-Yan Liu; Tao Qin 001; Xin Zheng; QianSheng Cheng; Wei-Ying Ma (ACM Multimedia, 2005)

Effective Feature Extraction for Play Detection in American Football Video. - Tie-Yan Liu; Wei-Ying Ma; HongJiang Zhang (MMM, 2005)

Subspace Clustering and Label Propagation for Active Feedback in Image Retrieval. - Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; Wei-Ying Ma; HongJiang Zhang (MMM, 2005)

A study of relevance propagation for web search. - Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; Zheng Chen 001; Wei-Ying Ma (SIGIR, 2005)

Webpage Importance Analysis Using Conditional Markov Random Walk. - Tie-Yan Liu; Wei-Ying Ma (Web Intelligence, 2005)

An Editor Labeling Model for Training Set Expansion in Web Categorization. - Tie-Yan Liu; Hao Wan 003; Wei-Ying Ma (Web Intelligence, 2005)

Site abstraction for rare category classification in large-scale web directory. - Tie-Yan Liu; Hao Wan 003; Tao Qin 001; Zheng Chen 001; Yong Ren; Wei-Ying Ma (WWW (Special interest tracks and posters), 2005)

An experimental study on large-scale web categorization. - Tie-Yan Liu; Yiming Yang; Hao Wan 003; Qian Zhou; Bin Gao 001; Hua-Jun Zeng; Zheng Chen 001; Wei-Ying Ma (WWW (Special interest tracks and posters), 2005)

Support vector machines classification with a very large-scale taxonomy. - Tie-Yan Liu; Yiming Yang; Hao Wan 003; Hua-Jun Zeng; Zheng Chen 001; Wei-Ying Ma (SIGKDD Explor., 2005)

Hierarchical Taxonomy Preparation for Text Categorization Using Consistent Bipartite Spectral Graph Copartitioning. - Bin Gao 001; Tie-Yan Liu; Guang Feng; Tao Qin 001; QianSheng Cheng; Wei-Ying Ma (IEEE Trans. Knowl. Data Eng., 2005)

Fast Spectral Clustering of Data Using Sequential Matrix Compression. - Bo Chen; Bin Gao 001; Tie-Yan Liu; Yu-Fu Chen; Wei-Ying Ma (ECML, 2006)

Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory. - Bin Gao 001; Tie-Yan Liu; Wei-Ying Ma (ICDM, 2006)

Detecting Link Spam Using Temporal Information. - Guoyang Shen; Bin Gao 001; Tie-Yan Liu; Guang Feng; Shiji Song; Hang Li 001 (ICDM, 2006)

Event detection from evolution of click-through data. - Qiankun Zhao; Tie-Yan Liu; Sourav S. Bhowmick; Wei-Ying Ma (KDD, 2006)

Level-Biased Statistics in the Hierarchical Structure of the Web. - Guang Feng; Tie-Yan Liu; Xudong Zhang 001; Wei-Ying Ma (PAKDD, 2006)

Heterogeneous Information Integration in Hierarchical Text Classification. - Huai-Yuan Yang; Tie-Yan Liu; Li Gao; Wei-Ying Ma (PAKDD, 2006)

Adapting ranking SVM to document retrieval. - Yunbo Cao; Jun Xu 001; Tie-Yan Liu; Hang Li 001; Yalou Huang; Hsiao-Wuen Hon (SIGIR, 2006)

AggregateRank: bringing order to web sites. - Guang Feng; Tie-Yan Liu; Ying Wang; Ying Bao; Zhiming Ma; Xu-Dong Zhang 001; Wei-Ying Ma (SIGIR, 2006)

Time-dependent semantic similarity measure of queries using historical click-through data. - Qiankun Zhao; Steven C. H. Hoi; Tie-Yan Liu; Sourav S. Bhowmick; Michael R. Lyu; Wei-Ying Ma (WWW, 2006)

Link analysis using time series of web graphs. - Lei Yang; Lei Qi; Yan-Ping Zhao; Bin Gao 001; Tie-Yan Liu (CIKM, 2007)

Fast Large-Scale Spectral Clustering by Sequential Shrinkage Optimization. - Tie-Yan Liu; Huai-Yuan Yang; Xin Zheng; Tao Qin 001; Wei-Ying Ma (ECIR, 2007)

N -Step PageRank for Web Search. - Li Zhang; Tao Qin 001; Tie-Yan Liu; Ying Bao; Hang Li 001 (ECIR, 2007)

Learning to rank: from pairwise approach to listwise approach. - Zhe Cao; Tao Qin 001; Tie-Yan Liu; Ming-Feng Tsai; Hang Li 001 (ICML, 2007)

Feature selection for ranking. - Xiubo Geng; Tie-Yan Liu; Tao Qin 001; Hang Li 001 (SIGIR, 2007)

Ranking with multiple hyperplanes. - Tao Qin 001; Xu-Dong Zhang 001; De-Sheng Wang; Tie-Yan Liu; Wei Lai; Hang Li 001 (SIGIR, 2007)

FRank: a ranking method with fidelity loss. - Ming-Feng Tsai; Tie-Yan Liu; Tao Qin 001; Hsin-Hsi Chen; Wei-Ying Ma (SIGIR, 2007)

Supervised rank aggregation. - Yuting Liu 002; Tie-Yan Liu; Tao Qin 001; Zhiming Ma; Hang Li 001 (WWW, 2007)

Ranking Websites: A Probabilistic View. - Ying Bao; Guang Feng; Tie-Yan Liu; Zhiming Ma; Ying Wang (Internet Math., 2007)

Topic distillation via sub-site retrieval. - Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; Guang Feng; De-Sheng Wang; Wei-Ying Ma (Inf. Process. Manag., 2007)

Learning to rank for information retrieval (LR4IR 2007). - Thorsten Joachims; Hang Li 001; Tie-Yan Liu; ChengXiang Zhai (SIGIR Forum, 2007)

Query-level stability and generalization in learning to rank. - Yanyan Lan; Tie-Yan Liu; Tao Qin 001; Zhiming Ma; Hang Li 001 (ICML, 2008)

Listwise approach to learning to rank: theory and algorithm. - Fen Xia; Tie-Yan Liu; Jue Wang 004; Wensheng Zhang 002; Hang Li 001 (ICML, 2008)

Global Ranking Using Continuous Conditional Random Fields. - Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; De-Sheng Wang; Hang Li 001 (NIPS, 2008)

Query dependent ranking using K-nearest neighbor. - Xiubo Geng; Tie-Yan Liu; Tao Qin 001; Andrew Arnold; Hang Li 001; Heung-Yeung Shum (SIGIR, 2008)

BrowseRank: letting web users vote for page importance. - Yuting Liu 002; Bin Gao 001; Tie-Yan Liu; Ying Zhang 015; Zhiming Ma; Shuyuan He; Hang Li 001 (SIGIR, 2008)

Directly optimizing evaluation measures in learning to rank. - Jun Xu 001; Tie-Yan Liu; Min Lu; Hang Li 001; Wei-Ying Ma (SIGIR, 2008)

Learning to rank relational objects and its application to web search. - Tao Qin 001; Tie-Yan Liu; Xu-Dong Zhang 001; De-Sheng Wang; Wen-Ying Xiong; Hang Li 001 (WWW, 2008)

Query-level loss functions for information retrieval. - Tao Qin 001; Xu-Dong Zhang 001; Ming-Feng Tsai; De-Sheng Wang; Tie-Yan Liu; Hang Li 001 (Inf. Process. Manag., 2008)

An active feedback framework for image retrieval. - Tao Qin 001; Xu-Dong Zhang 001; Tie-Yan Liu; De-Sheng Wang; Wei-Ying Ma; Hong-Jiang Zhang (Pattern Recognit. Lett., 2008)

Learning to rank for information retrieval (LR4IR 2008). - Hang Li 001; Tie-Yan Liu; ChengXiang Zhai (SIGIR Forum, 2008)

A general markov framework for page importance computation. - Bin Gao 001; Tie-Yan Liu; Zhiming Ma; Taifeng Wang; Hang Li 001 (CIKM, 2009)

Generalization analysis of listwise learning-to-rank algorithms. - Yanyan Lan; Tie-Yan Liu; Zhiming Ma; Hang Li 001 (ICML, 2009)

Ranking Measures and Loss Functions in Learning to Rank. - Wei Chen 034; Tie-Yan Liu; Yanyan Lan; Zhiming Ma; Hang Li 001 (NIPS, 2009)

Statistical Consistency of Top-k Ranking. - Fen Xia; Tie-Yan Liu; Hang Li 001 (NIPS, 2009)

Learning to Rank for Information Retrieval. - Tie-Yan Liu (Found. Trends Inf. Retr., 2009)

Learning to rank for information retrieval (LR4IR 2009). - Hang Li 001; Tie-Yan Liu; ChengXiang Zhai (SIGIR Forum, 2009)

Two-Layer Generalization Analysis for Ranking Using Rademacher Average. - Wei Chen 034; Tie-Yan Liu; Zhiming Ma (NIPS, 2010)

A New Probabilistic Model for Rank Aggregation. - Tao Qin 001; Xiubo Geng; Tie-Yan Liu (NIPS, 2010)

Ranking with query-dependent loss for web search. - Jiang Bian 002; Tie-Yan Liu; Tao Qin 001; Hongyuan Zha (WSDM, 2010)

Actively predicting diverse search intent from user browsing behaviors. - Zhicong Cheng; Bin Gao 001; Tie-Yan Liu (WWW, 2010)

Tendency correlation analysis for direct optimization of evaluation measures in information retrieval. - Yin He; Tie-Yan Liu (Inf. Retr., 2010)

Introduction to special issue on learning to rank for information retrieval. - Tie-Yan Liu; Thorsten Joachims; Hang Li 001; Chengxiang Zhai (Inf. Retr., 2010)

A framework to compute page importance based on user behaviors. - Yuting Liu 002; Tie-Yan Liu; Bin Gao 001; Zhiming Ma; Hang Li 001 (Inf. Retr., 2010)

A general approximation framework for direct optimization of information retrieval measures. - Tao Qin 001; Tie-Yan Liu; Hang Li 001 (Inf. Retr., 2010)

LETOR: A benchmark collection for research on learning to rank for information retrieval. - Tao Qin 001; Tie-Yan Liu; Jun Xu 001; Hang Li 001 (Inf. Retr., 2010)

Learning to Rank for Information Retrieval. - Tie-Yan Liu (Springer, 2011)

Semi-supervised ranking on very large graphs with rich metadata. - Bin Gao 001; Tie-Yan Liu; Wei Wei 002; Taifeng Wang; Hang Li 001 (KDD, 2011)

Let web spammers expose themselves. - Zhicong Cheng; Bin Gao 001; Congkai Sun; Yanbing Jiang; Tie-Yan Liu (WSDM, 2011)

Ranking on large-scale graphs with rich metadata. - Bin Gao 001; Taifeng Wang; Tie-Yan Liu (WWW (Companion Volume), 2011)

Selecting optimal training data for learning to rank. - Xiubo Geng; Tao Qin 001; Tie-Yan Liu; Xueqi Cheng; Hang Li 001 (Inf. Process. Manag., 2011)

Page importance computation based on Markov processes. - Bin Gao 001; Tie-Yan Liu; Yuting Liu 002; Taifeng Wang; Zhiming Ma; Hang Li 001 (Inf. Retr., 2011)

Future directions in learning to rank. - Olivier Chapelle; Yi Chang 001; Tie-Yan Liu (Yahoo! Learning to Rank Challenge, 2011)

A conversation with MSRA researchers. - Wei-Ying Ma; Tie-Yan Liu; Ji-Rong Wen; Zheng Chen 001; Zaiqing Nie; Xing Xie 001; Hang Li 001; Haixun Wang; Yu Zheng 004 (SIGKDD Explor., 2011)

A Study on Potential Head Advertisers in Sponsored Search. - Changhao Jiang; Min Zhang; Bin Gao 001; Tie-Yan Liu (AIRS, 2012)

A unified optimization framework for auction and guaranteed delivery in online advertising. - Konstantin Salomatin; Tie-Yan Liu; Yiming Yang (CIKM, 2012)

Joint optimization of bid and budget allocation in sponsored search. - Weinan Zhang 001; Ying Zhang 015; Bin Gao 001; Yong Yu 001; Xiaojie Yuan; Tie-Yan Liu (KDD, 2012)

Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space. - Yanyan Lan; Jiafeng Guo; Xueqi Cheng; Tie-Yan Liu (NIPS, 2012)

Large-scale graph mining and learning for information retrieval. - Bin Gao 001; Taifeng Wang; Tie-Yan Liu (SIGIR, 2012)

Convergence Analysis for Weighted Joint Strategy Fictitious Play in Generalized Second Price Auction. - Lei Yao; Wei Chen 034; Tie-Yan Liu (WINE, 2012)

Relational click prediction for sponsored search. - Chenyan Xiong; Taifeng Wang; Wenkui Ding; Yidong Shen; Tie-Yan Liu (WSDM, 2012)

A noise-tolerant graphical model for ranking. - Xiubo Geng; Tao Qin 001; Tie-Yan Liu; Xueqi Cheng (Inf. Process. Manag., 2012)

Multi-Armed Bandit with Budget Constraint and Variable Costs. - Wenkui Ding; Tao Qin 001; Xu-Dong Zhang 001; Tie-Yan Liu (AAAI, 2013)

A Theoretical Analysis of NDCG Type Ranking Measures. - Yining Wang 001; Liwei Wang 001; Yuanzhi Li; Di He 001; Tie-Yan Liu (COLT, 2013)

A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. - Di He 001; Wei Chen 034; Liwei Wang 001; Tie-Yan Liu (IJCAI, 2013)

Psychological advertising: exploring user psychology for click prediction in sponsored search. - Taifeng Wang; Jiang Bian 002; Shusen Liu; Yuyu Zhang; Tie-Yan Liu (KDD, 2013)

Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising. - Min Xu; Tao Qin 001; Tie-Yan Liu (NIPS, 2013)

Internet advertising: theory and practice. - Bin Gao 001; Jun Yan 001; Dou Shen; Tie-Yan Liu (SIGIR, 2013)

Optimal Allocation for Chunked-Reward Advertising. - Weihao Kong; Jian Li 015; Tie-Yan Liu; Tao Qin 001 (WINE, 2013)

Predicting advertiser bidding behaviors in sponsored search by rationality modeling. - Haifeng Xu; Bin Gao 001; Diyi Yang; Tie-Yan Liu (WWW, 2013)

$K$-anonymous Signaling Scheme. - Binyi Chen; Tao Qin 001; Tie-Yan Liu (CoRR, 2013)

Introducing LETOR 4.0 Datasets. - Tao Qin 001; Tie-Yan Liu (CoRR, 2013)

A Theoretical Analysis of NDCG Type Ranking Measures - Yining Wang 001; Liwei Wang 001; Yuanzhi Li; Di He 001; Tie-Yan Liu; Wei Chen 034 (CoRR, 2013)

Pure Price of Anarchy for Generalized Second Price Auction - Wenkui Ding; Tao Wu; Tao Qin 001; Tie-Yan Liu (CoRR, 2013)

Revenue Optimization for Group-Buying Websites - Weihao Kong; Jian Li 015; Tao Qin 001; Tie-Yan Liu (CoRR, 2013)

Online learning for auction mechanism in bandit setting. - Di He 001; Wei Chen 034; Liwei Wang 001; Tie-Yan Liu (Decis. Support Syst., 2013)

Learning Deep Representations for Graph Clustering. - Fei Tian; Bin Gao 001; Qing Cui; Enhong Chen; Tie-Yan Liu (AAAI, 2014)

Agent Behavior Prediction and Its Generalization Analysis. - Fei Tian; Haifang Li 002; Wei Chen 034; Tao Qin 001; Enhong Chen; Tie-Yan Liu (AAAI, 2014)

Incentivizing High-Quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium. - Yingce Xia; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (AAAI, 2014)

Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. - Yuyu Zhang; Hanjun Dai; Chang Xu 008; Jun Feng; Taifeng Wang; Jiang Bian 002; Bin Wang 004; Tie-Yan Liu (AAAI, 2014)

Generalized second price auctions with value externalities. - Weidong Ma; Tao Wu; Tao Qin 001; Tie-Yan Liu (AAMAS, 2014)

RC-NET: A General Framework for Incorporating Knowledge into Word Representations. - Chang Xu 008; Yalong Bai; Jiang Bian 002; Bin Gao 001; Gang Wang 001; Xiaoguang Liu 001; Tie-Yan Liu (CIKM, 2014)

Co-learning of Word Representations and Morpheme Representations. - Siyu Qiu; Qing Cui; Jiang Bian 002; Bin Gao 001; Tie-Yan Liu (COLING, 2014)

A Probabilistic Model for Learning Multi-Prototype Word Embeddings. - Fei Tian; Hanjun Dai; Jiang Bian 002; Bin Gao 001; Rui Zhang 052; Enhong Chen; Tie-Yan Liu (COLING, 2014)

Knowledge-Powered Deep Learning for Word Embedding. - Jiang Bian 002; Bin Gao 001; Tie-Yan Liu (ECML/PKDD (1), 2014)

Generalized second price auction with probabilistic broad match. - Wei Chen 034; Di He 001; Tie-Yan Liu; Tao Qin 001; Yixin Tao; Liwei Wang 001 (EC, 2014)

Sampling dilemma: towards effective data sampling for click prediction in sponsored search. - Jun Feng; Jiang Bian 002; Taifeng Wang; Wei Chen 034; Xiaoyan Zhu 001; Tie-Yan Liu (WSDM, 2014)

Learning Effective Word Embedding using Morphological Word Similarity. - Qing Cui; Bin Gao 001; Jiang Bian 002; Siyu Qiu; Tie-Yan Liu (CoRR, 2014)

WordRep: A Benchmark for Research on Learning Word Representations. - Bin Gao 001; Jiang Bian 002; Tie-Yan Liu (CoRR, 2014)

Generalization Analysis for Game-Theoretic Machine Learning. - Haifang Li 002; Fei Tian; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (CoRR, 2014)

Online Mechanism Design for Cloud Computing. - Weidong Ma; Bo Zheng; Tao Qin 001; Pingzhong Tang; Tie-Yan Liu (CoRR, 2014)

LightLDA: Big Topic Models on Modest Compute Clusters. - Jinhui Yuan; Fei Gao 018; Qirong Ho; Wei Dai 003; Jinliang Wei; Xun Zheng; Eric P. Xing; Tie-Yan Liu; Wei-Ying Ma (CoRR, 2014)

Bid keyword suggestion in sponsored search based on competitiveness and relevance. - Ying Zhang 015; Weinan Zhang 001; Bin Gao 001; Xiaojie Yuan; Tie-Yan Liu (Inf. Process. Manag., 2014)

Advertiser-centric approach to understand user click behavior in sponsored search. - Sungchul Kim; Tao Qin 001; Tie-Yan Liu; Hwanjo Yu (Inf. Sci., 2014)

Sponsored Search Auctions: Recent Advances and Future Directions. - Tao Qin 001; Wei Chen 034; Tie-Yan Liu (ACM Trans. Intell. Syst. Technol., 2014)

Generalization Analysis for Game-Theoretic Machine Learning. - Haifang Li 002; Fei Tian; Wei Chen 034; Tao Qin 001; Zhiming Ma; Tie-Yan Liu (AAAI, 2015)

Mechanism Learning with Mechanism Induced Data. - Tie-Yan Liu; Wei Chen 034; Tao Qin 001 (AAAI, 2015)

Preface. - Geoffrey Holmes 001; Tie-Yan Liu (ACML, 2015)

Mechanism Design for Daily Deals. - Binyi Chen; Tao Qin 001; Tie-Yan Liu (AAMAS, 2015)

New Mechanism for Reservation in Cloud Computing. - Changjun Wang; Weidong Ma; Tao Qin 001; Feidiao Yang; Tie-Yan Liu; Xujin Chen; Xiao-Dong Hu 001 (AAMAS, 2015)

Competitive Pricing for Cloud Computing in an Evolutionary Market. - Bolei Xu; Tao Qin 001; Guoping Qiu; Tie-Yan Liu (AAMAS, 2015)

Selling Reserved Instances in Cloud Computing. - Changjun Wang; Weidong Ma; Tao Qin 001; Xujin Chen; Xiaodong Hu 001; Tie-Yan Liu (IJCAI, 2015)

Thompson Sampling for Budgeted Multi-Armed Bandits. - Yingce Xia; Haifang Li 002; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (IJCAI, 2015)

Optimal Pricing for the Competitive and Evolutionary Cloud Market. - Bolei Xu; Tao Qin 001; Guoping Qiu; Tie-Yan Liu (IJCAI, 2015)

Listwise Collaborative Filtering. - Shanshan Huang 003; Shuaiqiang Wang; Tie-Yan Liu; Jun Ma 001; Zhumin Chen; Jari Veijalainen (SIGIR, 2015)

LightLDA: Big Topic Models on Modest Computer Clusters. - Jinhui Yuan; Fei Gao 018; Qirong Ho; Wei Dai 003; Jinliang Wei; Xun Zheng; Eric Poe Xing; Tie-Yan Liu; Wei-Ying Ma (WWW, 2015)

Large Margin Deep Neural Networks: Theory and Algorithms. - Shizhao Sun; Wei Chen 034; Liwei Wang 001; Tie-Yan Liu (CoRR, 2015)

Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding. - Huazheng Wang; Bin Gao 001; Jiang Bian 002; Fei Tian; Tie-Yan Liu (CoRR, 2015)

Global Optimization for Advertisement Selection in Sponsored Search. - Qing Cui; Feng-Shan Bai; Bin Gao 001; Tie-Yan Liu (J. Comput. Sci. Technol., 2015)

KNET: A General Framework for Learning Word Embedding Using Morphological Knowledge. - Qing Cui; Bin Gao 001; Jiang Bian 002; Siyu Qiu; Hanjun Dai; Tie-Yan Liu (ACM Trans. Inf. Syst., 2015)

On the Depth of Deep Neural Networks: A Theoretical View. - Shizhao Sun; Wei Chen 034; Liwei Wang 001; Xiaoguang Liu 001; Tie-Yan Liu (AAAI, 2016)

Online Non-Preemptive Story Scheduling in Web Advertising. - Tie-Yan Liu; Weidong Ma; Tao Qin 001; Pingzhong Tang; Guang Yang 020; Bo Zheng (AAMAS, 2016)

Optimal Sample Size for Adword Auctions: (Extended Abstract). - Jiang Rong; Tao Qin 001; Bo An 001; Tie-Yan Liu (AAMAS, 2016)

Best Action Selection in a Stochastic Environment. - Yingce Xia; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (AAMAS, 2016)

Modeling Bounded Rationality for Sponsored Search Auctions. - Jiang Rong; Tao Qin 001; Bo An 001; Tie-Yan Liu (ECAI, 2016)

Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding. - Huazheng Wang; Fei Tian; Bin Gao 001; Chengjieren Zhu; Jiang Bian 002; Tie-Yan Liu (EMNLP, 2016)

Bag-of-Entities Representation for Ranking. - Chenyan Xiong; Jamie Callan; Tie-Yan Liu (ICTIR, 2016)

Asynchronous Accelerated Stochastic Gradient Descent. - Qi Meng; Wei Chen 034; Jingcheng Yu; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (IJCAI, 2016)

Budgeted Multi-Armed Bandits with Multiple Plays. - Yingce Xia; Tao Qin 001; Weidong Ma; Nenghai Yu; Tie-Yan Liu (IJCAI, 2016)

Dual Learning for Machine Translation. - Di He 001; Yingce Xia; Tao Qin 001; Liwei Wang 001; Nenghai Yu; Tie-Yan Liu; Wei-Ying Ma (NIPS, 2016)

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks. - Xiang Li 041; Tao Qin 001; Jian Yang 003; Tie-Yan Liu (NIPS, 2016)

A Communication-Efficient Parallel Algorithm for Decision Tree. - Qi Meng; Guolin Ke; Taifeng Wang; Wei Chen 034; Qiwei Ye; Zhiming Ma; Tie-Yan Liu (NIPS, 2016)

Sentence Level Recurrent Topic Model: Letting Topics Speak for Themselves. - Fei Tian; Bin Gao 001; Di He 001; Tie-Yan Liu (CoRR, 2016)

Randomized Mechanisms for Selling Reserved Instances in Cloud. - Jia Zhang 004; Weidong Ma; Tao Qin 001; Xiaoming Sun 001; Tie-Yan Liu (CoRR, 2016)

Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. - Shuxin Zheng; Qi Meng; Taifeng Wang; Wei Chen 034; Nenghai Yu; Zhiming Ma; Tie-Yan Liu (CoRR, 2016)

Efficient Mechanism Design for Online Scheduling. - Xujin Chen; Xiaodong Hu 001; Tie-Yan Liu; Weidong Ma; Tao Qin 001; Pingzhong Tang; Changjun Wang; Bo Zheng (J. Artif. Intell. Res., 2016)

Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph. - Fei Tian; Bin Gao 001; Enhong Chen; Tie-Yan Liu (J. Comput. Sci. Technol., 2016)

Health Status Assessment and Failure Prediction for Hard Drives with Recurrent Neural Networks. - Chang Xu 008; Gang Wang 001; Xiaoguang Liu 001; Dongdong Guo; Tie-Yan Liu (IEEE Trans. Computers, 2016)

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information. - Wei Wei 002; Bin Gao 001; Tie-Yan Liu; Taifeng Wang; Guohui Li 001; Hang Li 001 (IEEE Trans. Cybern., 2016)

Ranking-Oriented Collaborative Filtering: A Listwise Approach. - Shuaiqiang Wang; Shanshan Huang 003; Tie-Yan Liu; Jun Ma 001; Zhumin Chen; Jari Veijalainen (ACM Trans. Inf. Syst., 2016)

Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. - Qi Meng; Wei Chen 034; Jingcheng Yu; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (AAAI, 2017)

Generalization Error Bounds for Optimization Algorithms via Stability. - Qi Meng; Yue Wang 017; Wei Chen 034; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (AAAI, 2017)

Revenue Maximization for Finitely Repeated Ad Auctions. - Jiang Rong; Tao Qin 001; Bo An 001; Tie-Yan Liu (AAAI, 2017)

Randomized Mechanisms for Selling Reserved Instances in Cloud Computing. - Jia Zhang 004; Weidong Ma; Tao Qin 001; Xiaoming Sun 001; Tie-Yan Liu (AAAI, 2017)

Pricing Optimization for Selling Reusable Resources. - Jiang Rong; Tao Qin 001; Bo An 001; Tie-Yan Liu (AAMAS, 2017)

Convolutional neural networks for posed and spontaneous expression recognition. - Chang Xu 008; Tao Qin 001; Yalong Bai; Gang Wang 001; Tie-Yan Liu (ICME, 2017)

Dual Supervised Learning. - Yingce Xia; Tao Qin 001; Wei Chen 034; Jiang Bian 002; Nenghai Yu; Tie-Yan Liu (ICML, 2017)

Asynchronous Stochastic Gradient Descent with Delay Compensation. - Shuxin Zheng; Qi Meng; Taifeng Wang; Wei Chen 034; Nenghai Yu; Zhiming Ma; Tie-Yan Liu (ICML, 2017)

Efficient Mechanism Design for Online Scheduling (Extended Abstract). - Xujin Chen; Xiaodong Hu 001; Tie-Yan Liu; Weidong Ma; Tao Qin 001; Pingzhong Tang; Changjun Wang; Bo Zheng (IJCAI, 2017)

Sequence Prediction with Unlabeled Data by Reward Function Learning. - Lijun Wu 003; Li Zhao 007; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (IJCAI, 2017)

Dual Inference for Machine Learning. - Yingce Xia; Jiang Bian 002; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (IJCAI, 2017)

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. - Quanming Yao; James T. Kwok; Fei Gao 018; Wei Chen 034; Tie-Yan Liu (IJCAI, 2017)

Decoding with Value Networks for Neural Machine Translation. - Di He 001; Hanqing Lu; Yingce Xia; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (NIPS, 2017)

LightGBM: A Highly Efficient Gradient Boosting Decision Tree. - Guolin Ke; Qi Meng; Thomas Finley; Taifeng Wang; Wei Chen 034; Weidong Ma; Qiwei Ye; Tie-Yan Liu (NIPS, 2017)

Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting. - Yue Wang 017; Wei Chen 034; Yuting Liu 002; Zhiming Ma; Tie-Yan Liu (NIPS, 2017)

Deliberation Networks: Sequence Generation Beyond One-Pass Decoding. - Yingce Xia; Fei Tian; Lijun Wu 003; Jianxin Lin; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (NIPS, 2017)

Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. - Shizhao Sun; Wei Chen 034; Jiang Bian 002; Xiaoguang Liu 001; Tie-Yan Liu (ECML/PKDD (1), 2017)

Sequence Generation with Target Attention. - Yingce Xia; Fei Tian; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (ECML/PKDD (1), 2017)

Word-Entity Duet Representations for Document Ranking. - Chenyan Xiong; Jamie Callan; Tie-Yan Liu (SIGIR, 2017)

Scale Effects in Web Search. - Di He 001; Aadharsh Kannan; Tie-Yan Liu; R. Preston McAfee; Tao Qin 001; Justin M. Rao (WINE, 2017)

Distributed Machine Learning: Foundations, Trends, and Practices. - Tie-Yan Liu; Wei Chen 034; Taifeng Wang (WWW (Companion Volume), 2017)

Learning What Data to Learn. - Yang Fan; Fei Tian; Tao Qin 001; Jiang Bian 002; Tie-Yan Liu (CoRR, 2017)

Reinforcement Learning for Learning Rate Control. - Chang Xu 008; Tao Qin 001; Gang Wang 001; Tie-Yan Liu (CoRR, 2017)

Slim-DP: A Light Communication Data Parallelism for DNN. - Shizhao Sun; Wei Chen 034; Jiang Bian 002; Xiaoguang Liu 001; Tie-Yan Liu (CoRR, 2017)

Finite budget analysis of multi-armed bandit problems. - Yingce Xia; Tao Qin 001; Wenkui Ding; Haifang Li 002; Xudong Zhang 001; Nenghai Yu; Tie-Yan Liu (Neurocomputing, 2017)

Introduction: special issue of selected papers from ACML 2015. - Geoffrey Holmes 001; Tie-Yan Liu; Hang Li 001; Irwin King; Masashi Sugiyama; Zhi-Hua Zhou (Mach. Learn., 2017)

Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization. - Yijun Wang 002; Yingce Xia; Li Zhao 007; Jiang Bian 002; Tao Qin 001; Guiquan Liu; Tie-Yan Liu (AAAI, 2018)

Word Attention for Sequence to Sequence Text Understanding. - Lijun Wu 003; Fei Tian; Li Zhao 007; Jianhuang Lai; Tie-Yan Liu (AAAI, 2018)

Adversarial Neural Machine Translation. - Lijun Wu 003; Yingce Xia; Fei Tian; Li Zhao 007; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (ACML, 2018)

Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems. - Feidiao Yang; Tiancheng Jin; Tie-Yan Liu; Xiaoming Sun 001; Jialin Zhang 001 (ACML, 2018)

Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. - Shizhao Sun; Wei Chen 034; Jiang Bian 002; Xiaoguang Liu 001; Tie-Yan Liu (AAMAS, 2018)

Double Path Networks for Sequence to Sequence Learning. - Kaitao Song; Xu Tan 003; Di He 001; Jianfeng Lu 003; Tao Qin 001; Tie-Yan Liu (COLING, 2018)

Conditional Image-to-Image Translation. - Jianxin Lin; Yingce Xia; Tao Qin 001; Zhibo Chen 001; Tie-Yan Liu (CVPR, 2018)

Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. - Lijun Wu 003; Xu Tan 003; Di He 001; Fei Tian; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (EMNLP, 2018)

A Study of Reinforcement Learning for Neural Machine Translation. - Lijun Wu 003; Fei Tian; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (EMNLP, 2018)

Learning to Teach. - Yang Fan; Fei Tian; Tao Qin 001; Xiang-Yang Li 001; Tie-Yan Liu (ICLR (Poster), 2018)

Towards Binary-Valued Gates for Robust LSTM Training. - Zhuohan Li 001; Di He 001; Fei Tian; Wei Chen 034; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (ICML, 2018)

Model-Level Dual Learning. - Yingce Xia; Xu Tan 003; Fei Tian; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (ICML, 2018)

Differential Equations for Modeling Asynchronous Algorithms. - Li He; Qi Meng; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (IJCAI, 2018)

Investor-Imitator: A Framework for Trading Knowledge Extraction. - Yi Ding; Weiqing Liu; Jiang Bian 002; Daoqiang Zhang; Tie-Yan Liu (KDD, 2018)

Efficient Sequence Learning with Group Recurrent Networks. - Fei Gao 018; Lijun Wu 003; Li Zhao 007; Tao Qin 001; Xueqi Cheng; Tie-Yan Liu (NAACL-HLT, 2018)

Dense Information Flow for Neural Machine Translation. - Yanyao Shen; Xu Tan 003; Di He 001; Tao Qin 001; Tie-Yan Liu (NAACL-HLT, 2018)

FRAGE: Frequency-Agnostic Word Representation. - ChengYue Gong; Di He 001; Xu Tan 003; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (NeurIPS, 2018)

Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation. - Tianyu He; Xu Tan 003; Yingce Xia; Di He 001; Tao Qin 001; Zhibo Chen 001; Tie-Yan Liu (NeurIPS, 2018)

Neural Architecture Optimization. - Renqian Luo; Fei Tian; Tao Qin 001; Enhong Chen; Tie-Yan Liu (NeurIPS, 2018)

Learning to Teach with Dynamic Loss Functions. - Lijun Wu 003; Fei Tian; Yingce Xia; Yang Fan; Tao Qin 001; Jian-Huang Lai; Tie-Yan Liu (NeurIPS, 2018)

On the Local Hessian in Back-propagation. - Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2018)

Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling. - Chenyan Xiong; Zhengzhong Liu 001; Jamie Callan; Tie-Yan Liu (SIGIR, 2018)

Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction. - Ziniu Hu; Weiqing Liu; Jiang Bian 002; Xuanzhe Liu; Tie-Yan Liu (WSDM, 2018)

Optimizing Neural Networks in the Equivalent Class Space. - Qi Meng; Wei Chen 034; Shuxin Zheng; Qiwei Ye; Tie-Yan Liu (CoRR, 2018)

Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. - Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (CoRR, 2018)

Achieving Human Parity on Automatic Chinese to English News Translation. - Hany Hassan; Anthony Aue; Chang Chen; Vishal Chowdhary; Jonathan Clark; Christian Federmann; Xuedong Huang 001; Marcin Junczys-Dowmunt; William Lewis; Mu Li 001; Shujie Liu 001; Tie-Yan Liu; et al. (CoRR, 2018)

Neural Architecture Optimization. - Renqian Luo; Fei Tian; Tao Qin 001; Tie-Yan Liu (CoRR, 2018)

Target Transfer Q-Learning and Its Convergence Analysis. - Yue Wang 017; Qi Meng; Wei Chen 034; Yuting Liu 002; Zhiming Ma; Tie-Yan Liu (CoRR, 2018)

Computational pricing in Internet era. - Fei Tian; Tao Qin 001; Tie-Yan Liu (Frontiers Comput. Sci., 2018)

Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. - Junliang Guo; Xu Tan 003; Di He 001; Tao Qin 001; Linli Xu; Tie-Yan Liu (AAAI, 2019)

Trust Region Evolution Strategies. - Guoqing Liu; Li Zhao 007; Feidiao Yang; Jiang Bian 002; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (AAAI, 2019)

Non-Autoregressive Machine Translation with Auxiliary Regularization. - Yiren Wang; Fei Tian; Di He 001; Tao Qin 001; ChengXiang Zhai; Tie-Yan Liu (AAAI, 2019)

Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks. - Chang Xu 008; Weiran Huang 001; Hongwei Wang 004; Gang Wang 001; Tie-Yan Liu (AAAI, 2019)

Capacity Control of ReLU Neural Networks by Basis-Path Norm. - Shuxin Zheng; Qi Meng; Huishuai Zhang; Wei Chen 034; Nenghai Yu; Tie-Yan Liu (AAAI, 2019)

Soft Contextual Data Augmentation for Neural Machine Translation. - Fei Gao 018; Jinhua Zhu 001; Lijun Wu 003; Yingce Xia; Tao Qin 001; Xueqi Cheng; Wengang Zhou 001; Tie-Yan Liu (ACL (1), 2019)

Unsupervised Pivot Translation for Distant Languages. - Yichong Leng; Xu Tan 003; Tao Qin 001; Xiang-Yang Li 001; Tie-Yan Liu (ACL (1), 2019)

Depth Growing for Neural Machine Translation. - Lijun Wu 003; Yiren Wang; Yingce Xia; Fei Tian; Fei Gao 018; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (ACL (1), 2019)

Knowledge Distillation from Bert in Pre-Training and Fine-Tuning for Polyphone Disambiguation. - Hao Sun; Xu Tan 003; Jun-Wei Gan; Sheng Zhao; Dongxu Han; Hongzhi Liu 001; Tao Qin 001; Tie-Yan Liu (ASRU, 2019)

A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. - Xihan Li 001; Jia Zhang 004; Jiang Bian 002; Yunhai Tong; Tie-Yan Liu (AAMAS, 2019)

Hint-Based Training for Non-Autoregressive Machine Translation. - Zhuohan Li 001; Zi Lin; Di He 001; Fei Tian; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (EMNLP/IJCNLP (1), 2019)

Multilingual Neural Machine Translation with Language Clustering. - Xu Tan 003; Jiale Chen 001; Di He 001; Yingce Xia; Tao Qin 001; Tie-Yan Liu (EMNLP/IJCNLP (1), 2019)

Exploiting Monolingual Data at Scale for Neural Machine Translation. - Lijun Wu 003; Yiren Wang; Yingce Xia; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (EMNLP/IJCNLP (1), 2019)

Machine Translation With Weakly Paired Documents. - Lijun Wu 003; Jinhua Zhu 001; Di He 001; Fei Gao 018; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (EMNLP/IJCNLP (1), 2019)

Representation Degeneration Problem in Training Natural Language Generation Models. - Jun Gao 004; Di He 001; Xu Tan 003; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (ICLR (Poster), 2019)

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. - Qi Meng; Shuxin Zheng; Huishuai Zhang; Wei Chen 034; Qiwei Ye; Zhi-Ming Ma; Nenghai Yu; Tie-Yan Liu (ICLR (Poster), 2019)

Multilingual Neural Machine Translation with Knowledge Distillation. - Xu Tan 003; Yi Ren 006; Di He 001; Tao Qin 001; Zhou Zhao 001; Tie-Yan Liu (ICLR (Poster), 2019)

Multi-Agent Dual Learning. - Yiren Wang; Yingce Xia; Tianyu He; Fei Tian; Tao Qin 001; ChengXiang Zhai; Tie-Yan Liu (ICLR (Poster), 2019)

Efficient Training of BERT by Progressively Stacking. - Linyuan Gong; Di He 001; Zhuohan Li 001; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (ICML, 2019)

Almost Unsupervised Text to Speech and Automatic Speech Recognition. - Yi Ren 006; Xu Tan 003; Tao Qin 001; Sheng Zhao; Zhou Zhao 001; Tie-Yan Liu (ICML, 2019)

MASS: Masked Sequence to Sequence Pre-training for Language Generation. - Kaitao Song; Xu Tan 003; Tao Qin 001; Jianfeng Lu 003; Tie-Yan Liu (ICML, 2019)

Adaptive Regret of Convex and Smooth Functions. - Lijun Zhang 005; Tie-Yan Liu; Zhi-Hua Zhou (ICML, 2019)

Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models. - Chang Xu 008; Tao Qin 001; Gang Wang 001; Tie-Yan Liu (IJCAI, 2019)

BN-invariant Sharpness Regularizes the Training Model to Better Generalization. - Mingyang Yi; Huishuai Zhang; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (IJCAI, 2019)

Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion. - Hao Sun; Xu Tan 003; Jun-Wei Gan; Hongzhi Liu 001; Sheng Zhao; Tao Qin 001; Tie-Yan Liu (INTERSPEECH, 2019)

Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. - Chi Chen; Li Zhao 007; Jiang Bian 002; Chunxiao Xing; Tie-Yan Liu (KDD, 2019)

DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. - Guolin Ke; Zhenhui Xu; Jia Zhang 004; Jiang Bian 002; Tie-Yan Liu (KDD, 2019)

Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. - Zhige Li; Derek Yang; Li Zhao 007; Jiang Bian 002; Tao Qin 001; Tie-Yan Liu (KDD, 2019)

Normalization Helps Training of Quantized LSTM. - Lu Hou 002; Jinhua Zhu 001; James T. Kwok; Fei Gao 018; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2019)

Distributional Reward Decomposition for Reinforcement Learning. - Zichuan Lin; Li Zhao 007; Derek Yang; Tao Qin 001; Tie-Yan Liu; Guangwen Yang (NeurIPS, 2019)

FastSpeech: Fast, Robust and Controllable Text to Speech. - Yi Ren 006; Yangjun Ruan; Xu Tan 003; Tao Qin 001; Sheng Zhao; Zhou Zhao 001; Tie-Yan Liu (NeurIPS, 2019)

Neural Machine Translation with Soft Prototype. - Yiren Wang; Yingce Xia; Fei Tian; Fei Gao 018; Tao Qin 001; ChengXiang Zhai; Tie-Yan Liu (NeurIPS, 2019)

Fully Parameterized Quantile Function for Distributional Reinforcement Learning. - Derek Yang; Li Zhao 007; Zichuan Lin; Tao Qin 001; Jiang Bian 002; Tie-Yan Liu (NeurIPS, 2019)

Microsoft Research Asia's Systems for WMT19. - Yingce Xia; Xu Tan 003; Fei Tian; Fei Gao 018; Di He 001; Weicong Chen; Yang Fan; Linyuan Gong; Yichong Leng; Renqian Luo; Yiren Wang; Lijun Wu 003; et al. (WMT (2), 2019)

Positively Scale-Invariant Flatness of ReLU Neural Networks. - Mingyang Yi; Qi Meng; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2019)

Reinforcement Learning with Dynamic Boltzmann Softmax Updates. - Ling Pan; Qingpeng Cai 001; Qi Meng; Wei Chen 034; Longbo Huang; Tie-Yan Liu (CoRR, 2019)

Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. - Huishuai Zhang; Da Yu; Wei Chen 034; Tie-Yan Liu (CoRR, 2019)

Learning Efficient and Effective Exploration Policies with Counterfactual Meta Policy. - Ruihan Yang; Qiwei Ye; Tie-Yan Liu (CoRR, 2019)

Beyond Exponentially Discounted Sum: Automatic Learning of Return Function. - Yufei Wang; Qiwei Ye; Tie-Yan Liu (CoRR, 2019)

Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View. - Yiping Lu 001; Zhuohan Li 001; Di He 001; Zhiqing Sun; Bin Dong 001; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (CoRR, 2019)

LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm. - Ziyu Liu; Guolin Ke; Jiang Bian 002; Tie-Yan Liu (CoRR, 2019)

Microsoft Research Asia's Systems for WMT19. - Yingce Xia; Xu Tan 003; Fei Tian; Fei Gao 018; Weicong Chen; Yang Fan; Linyuan Gong; Yichong Leng; Renqian Luo; Yiren Wang; Lijun Wu 003; Jinhua Zhu 001; et al. (CoRR, 2019)

A Study of Multilingual Neural Machine Translation. - Xu Tan 003; Yichong Leng; Jiale Chen 001; Yi Ren 006; Tao Qin 001; Tie-Yan Liu (CoRR, 2019)

OptQuant: Distributed training of neural networks with optimized quantization mechanisms. - Li He; Shuxin Zheng; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (Neurocomputing, 2019)

Convergence analysis of distributed stochastic gradient descent with shuffling. - Qi Meng; Wei Chen 034; Yue Wang 017; Zhi-Ming Ma; Tie-Yan Liu (Neurocomputing, 2019)

Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. - Quanming Yao; James T. Kwok; Taifeng Wang; Tie-Yan Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation. - Yijun Wang 002; Yingce Xia; Li Zhao 007; Jiang Bian 002; Tao Qin 001; Enhong Chen; Tie-Yan Liu (IEEE ACM Trans. Audio Speech Lang. Process., 2019)

Beyond Error Propagation: Language Branching Also Affects the Accuracy of Sequence Generation. - Lijun Wu 003; Xu Tan 003; Tao Qin 001; Jianhuang Lai; Tie-Yan Liu (IEEE ACM Trans. Audio Speech Lang. Process., 2019)

Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. - Junliang Guo; Xu Tan 003; Linli Xu; Tao Qin 001; Enhong Chen; Tie-Yan Liu (AAAI, 2020)

Transductive Ensemble Learning for Neural Machine Translation. - Yiren Wang; Lijun Wu 003; Yingce Xia; Tao Qin 001; ChengXiang Zhai; Tie-Yan Liu (AAAI, 2020)

Light Multi-Segment Activation for Model Compression. - Zhenhui Xu; Guolin Ke; Jia Zhang 004; Jiang Bian 002; Tie-Yan Liu (AAAI, 2020)

SimulSpeech: End-to-End Simultaneous Speech to Text Translation. - Yi Ren 006; Jinglin Liu; Xu Tan 003; Chen Zhang 020; Tao Qin 001; Zhou Zhao 001; Tie-Yan Liu (ACL, 2020)

A Study of Non-autoregressive Model for Sequence Generation. - Yi Ren 006; Jinglin Liu; Xu Tan 003; Zhou Zhao 001; Sheng Zhao; Tie-Yan Liu (ACL, 2020)

SEEK: Segmented Embedding of Knowledge Graphs. - Wentao Xu; Shun Zheng 001; Liang He 010; Bin Shao; Jian Yin 001; Tie-Yan Liu (ACL, 2020)

Invertible Image Rescaling. - Mingqing Xiao 002; Shuxin Zheng; Chang Liu 030; Yaolong Wang; Di He 001; Guolin Ke; Jiang Bian 002; Zhouchen Lin; Tie-Yan Liu (ECCV (1), 2020)

Self-paced Ensemble for Highly Imbalanced Massive Data Classification. - Zhining Liu 002; Wei Cao 007; Zhifeng Gao; Jiang Bian 002; Hechang Chen; Yi Chang 001; Tie-Yan Liu (ICDE, 2020)

Incorporating BERT into Neural Machine Translation. - Jinhua Zhu 001; Yingce Xia; Lijun Wu 003; Di He 001; Tao Qin 001; Wengang Zhou 001; Houqiang Li; Tie-Yan Liu (ICLR, 2020)

Sequence Generation with Mixed Representations. - Lijun Wu 003; Shufang Xie 003; Yingce Xia; Yang Fan; Jian-Huang Lai; Tao Qin 001; Tie-Yan Liu (ICML, 2020)

On Layer Normalization in the Transformer Architecture. - Ruibin Xiong; Yunchang Yang; Di He 001; Kai Zheng 007; Shuxin Zheng; Chen Xing; Huishuai Zhang; Yanyan Lan; Liwei Wang 001; Tie-Yan Liu (ICML, 2020)

Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation. - Jinglin Liu; Yi Ren 006; Xu Tan 003; Chen Zhang 020; Tao Qin 001; Zhou Zhao 001; Tie-Yan Liu (IJCAI, 2020)

Gradient Perturbation is Underrated for Differentially Private Convex Optimization. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (IJCAI, 2020)

DeepSinger: Singing Voice Synthesis with Data Mined From the Web. - Yi Ren 006; Xu Tan 003; Tao Qin 001; Jian Luan 001; Zhou Zhao 001; Tie-Yan Liu (KDD, 2020)

LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition. - Jin Xu 010; Xu Tan 003; Yi Ren 006; Tao Qin 001; Jian Li 015; Sheng Zhao; Tie-Yan Liu (KDD, 2020)

DualLip: A System for Joint Lip Reading and Generation. - Weicong Chen; Xu Tan 003; Yingce Xia; Tao Qin 001; Yu Wang 002; Tie-Yan Liu (ACM Multimedia, 2020)

PopMAG: Pop Music Accompaniment Generation. - Yi Ren 006; Jinzheng He; Xu Tan 003; Tao Qin 001; Zhou Zhao 001; Tie-Yan Liu (ACM Multimedia, 2020)

RD$^2$: Reward Decomposition with Representation Decomposition. - Zichuan Lin; Derek Yang; Li Zhao 007; Tao Qin 001; Guangwen Yang; Tie-Yan Liu (NeurIPS, 2020)

Semi-Supervised Neural Architecture Search. - Renqian Luo; Xu Tan 003; Rui Wang 028; Tao Qin 001; Enhong Chen; Tie-Yan Liu (NeurIPS, 2020)

MPNet: Masked and Permuted Pre-training for Language Understanding. - Kaitao Song; Xu Tan 003; Tao Qin 001; Jianfeng Lu 003; Tie-Yan Liu (NeurIPS, 2020)

Suphx: Mastering Mahjong with Deep Reinforcement Learning. - Junjie Li; Sotetsu Koyamada; Qiwei Ye; Guoqing Liu; Chao Wang; Ruihan Yang; Li Zhao 007; Tao Qin 001; Tie-Yan Liu; Hsiao-Wuen Hon (CoRR, 2020)

Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator. - Yuxuan Song; Qiwei Ye; Minkai Xu; Tie-Yan Liu (CoRR, 2020)

LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning. - Kaitao Song; Hao Sun; Xu Tan 003; Tao Qin 001; Jianfeng Lu 003; Hongzhi Liu 001; Tie-Yan Liu (CoRR, 2020)

MC-BERT: Efficient Language Pre-Training via a Meta Controller. - Zhenhui Xu; Linyuan Gong; Guolin Ke; Di He 001; Shuxin Zheng; Liwei Wang 001; Jiang Bian 002; Tie-Yan Liu (CoRR, 2020)

Multi-branch Attentive Transformer. - Yang Fan; Shufang Xie 003; Yingce Xia; Lijun Wu 003; Tao Qin 001; Xiang-Yang Li 001; Tie-Yan Liu (CoRR, 2020)

Modeling Lost Information in Lossy Image Compression. - Yaolong Wang; Mingqing Xiao 002; Chang Liu 030; Shuxin Zheng; Tie-Yan Liu (CoRR, 2020)

Dynamic of Stochastic Gradient Descent with State-Dependent Noise. - Qi Meng; Shiqi Gong; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2020)

Learning to Teach with Deep Interactions. - Yang Fan; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Weiqing Liu; Jiang Bian 002; Tao Qin 001; Xiang-Yang Li 001; Tie-Yan Liu (CoRR, 2020)

Neural Architecture Search with GBDT. - Renqian Luo; Xu Tan 003; Rui Wang 028; Tao Qin 001; Enhong Chen; Tie-Yan Liu (CoRR, 2020)

Learn to Use Future Information in Simultaneous Translation. - Xueqing Wu 001; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Weiqing Liu; Jiang Bian 002; Tao Qin 001; Tie-Yan Liu (CoRR, 2020)

Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (CoRR, 2020)

Learning to Match Distributions for Domain Adaptation. - Chaohui Yu; Jindong Wang 001; Chang Liu 030; Tao Qin 001; Renjun Xu; Wenjie Feng 001; Yiqiang Chen 001; Tie-Yan Liu (CoRR, 2020)

Taking Notes on the Fly Helps BERT Pre-training. - Qiyu Wu 001; Chen Xing; Yatao Li; Guolin Ke; Di He 001; Tie-Yan Liu (CoRR, 2020)

HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis. - Jiawei Chen 008; Xu Tan 003; Jian Luan 001; Tao Qin 001; Tie-Yan Liu (CoRR, 2020)

Qlib: An AI-oriented Quantitative Investment Platform. - Xiao Yang; Weiqing Liu; Dong Zhou; Jiang Bian 002; Tie-Yan Liu (CoRR, 2020)

COSEA: Convolutional Code Search with Layer-wise Attention. - Hao Wang 003; Jia Zhang 004; Yingce Xia; Jiang Bian 002; Chao Zhang 008; Tie-Yan Liu (CoRR, 2020)

Learning Causal Semantic Representation for Out-of-Distribution Prediction. - Chang Liu 030; Xinwei Sun 001; Jindong Wang 001; Tao Li 040; Tao Qin 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2020)

Latent Causal Invariant Model. - Xinwei Sun 001; Botong Wu; Chang Liu 030; Xiangyu Zheng; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (CoRR, 2020)

Target transfer Q-learning and its convergence analysis. - Yue Wang 017; Yuting Liu 002; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (Neurocomputing, 2020)

Searching Better Architectures for Neural Machine Translation. - Yang Fan; Fei Tian; Yingce Xia; Tao Qin 001; Xiang-Yang Li 001; Tie-Yan Liu (IEEE ACM Trans. Audio Speech Lang. Process., 2020)

Automatically Design Convolutional Neural Networks by Optimization With Submodularity and Supermodularity. - Wenzheng Hu; Junqi Jin; Tie-Yan Liu; Changshui Zhang (IEEE Trans. Neural Networks Learn. Syst., 2020)

Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. - Shicong Cen; Huishuai Zhang; Yuejie Chi; Wei Chen 034; Tie-Yan Liu (IEEE Trans. Signal Process., 2020)

Universal Trading for Order Execution with Oracle Policy Distillation. - Yuchen Fang; Kan Ren; Weiqing Liu; Dong Zhou; Weinan Zhang 001; Jiang Bian 002; Yong Yu 001; Tie-Yan Liu (AAAI, 2021)

How Does Data Augmentation Affect Privacy in Machine Learning? - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (AAAI, 2021)

UWSpeech: Speech to Speech Translation for Unwritten Languages. - Chen Zhang 020; Xu Tan 003; Yi Ren 006; Tao Qin 001; Kejun Zhang; Tie-Yan Liu (AAAI, 2021)

DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. - Lanqing Xue; Kaitao Song; Duocai Wu; Xu Tan 003; Nevin L. Zhang; Tao Qin 001; Wei-Qiang Zhang; Tie-Yan Liu (ACL/IJCNLP (1), 2021)

MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training. - Mingliang Zeng; Xu Tan 003; Rui Wang 028; Zeqian Ju; Tao Qin 001; Tie-Yan Liu (ACL/IJCNLP (Findings), 2021)

Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. - Wenlei Shi; Xinran Wei; Jia Zhang 004; Xiaoyuan Ni; Arthur Jiang; Jiang Bian 002; Tie-Yan Liu (AAMAS, 2021)

Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion. - Min Hou; Chang Xu 008; Yang Liu 278; Weiqing Liu; Jiang Bian 002; Le Wu; Zhi Li 057; Enhong Chen; Tie-Yan Liu (CIKM, 2021)

HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. - Shun Zheng 001; Zhifeng Gao; Wei Cao 007; Jiang Bian 002; Tie-Yan Liu (CIKM, 2021)

FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. - Yichong Leng; Xu Tan 003; Rui Wang 028; Linchen Zhu; Jin Xu 010; Wenjie Liu; Linquan Liu; Xiang-Yang Li 001; Tao Qin 001; Edward Lin; Tie-Yan Liu (EMNLP (Findings), 2021)

Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder. - Shuqi Lu; Di He 001; Chenyan Xiong; Guolin Ke; Waleed Malik; Zhicheng Dou; Paul Bennett 001; Tie-Yan Liu; Arnold Overwijk (EMNLP (1), 2021)

Lightspeech: Lightweight and Fast Text to Speech with Neural Architecture Search. - Renqian Luo; Xu Tan 003; Rui Wang 028; Tao Qin 001; Jinzhu Li; Sheng Zhao; Enhong Chen; Tie-Yan Liu (ICASSP, 2021)

Adaspeech 2: Adaptive Text to Speech with Untranscribed Data. - Yuzi Yan; Xu Tan 003; Bohan Li 003; Tao Qin 001; Sheng Zhao; Yuan Shen 001; Tie-Yan Liu (ICASSP, 2021)

Denoispeech: Denoising Text to Speech with Frame-Level Noise Modeling. - Chen Zhang 020; Yi Ren 006; Xu Tan 003; Jinglin Liu; Kejun Zhang; Tao Qin 001; Sheng Zhao; Tie-Yan Liu (ICASSP, 2021)

Taking Notes on the Fly Helps Language Pre-Training. - Qiyu Wu 001; Chen Xing; Yatao Li; Guolin Ke; Di He 001; Tie-Yan Liu (ICLR, 2021)

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech. - Yi Ren 006; Chenxu Hu; Xu Tan 003; Tao Qin 001; Sheng Zhao; Zhou Zhao 001; Tie-Yan Liu (ICLR, 2021)

AdaSpeech: Adaptive Text to Speech for Custom Voice. - Mingjian Chen; Xu Tan 003; Bohan Li 003; Yanqing Liu; Tao Qin 001; Sheng Zhao; Tie-Yan Liu (ICLR, 2021)

Rethinking Positional Encoding in Language Pre-training. - Guolin Ke; Di He 001; Tie-Yan Liu (ICLR, 2021)

Return-Based Contrastive Representation Learning for Reinforcement Learning. - Guoqing Liu; Chuheng Zhang; Li Zhao 007; Tao Qin 001; Jinhua Zhu 001; Jian Li 015; Nenghai Yu; Tie-Yan Liu (ICLR, 2021)

Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. - Da Yu; Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (ICLR, 2021)

IOT: Instance-wise Layer Reordering for Transformer Structures. - Jinhua Zhu 001; Lijun Wu 003; Yingce Xia; Shufang Xie 003; Tao Qin 001; Wengang Zhou 001; Houqiang Li; Tie-Yan Liu (ICLR, 2021)

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. - Tianle Cai; Shengjie Luo; Keyulu Xu; Di He 001; Tie-Yan Liu; Liwei Wang 001 (ICML, 2021)

How could Neural Networks understand Programs? - Dinglan Peng; Shuxin Zheng; Yatao Li; Guolin Ke; Di He 001; Tie-Yan Liu (ICML, 2021)

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. - Bohan Wang; Qi Meng; Wei Chen 034; Tie-Yan Liu (ICML, 2021)

Temporally Correlated Task Scheduling for Sequence Learning. - Xueqing Wu 001; Lewen Wang; Yingce Xia; Weiqing Liu; Lijun Wu 003; Shufang Xie 003; Tao Qin 001; Tie-Yan Liu (ICML, 2021)

Large Scale Private Learning via Low-rank Reparametrization. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (ICML, 2021)

A Survey on Low-Resource Neural Machine Translation. - Rui Wang 028; Xu Tan 003; Renqian Luo; Tao Qin 001; Tie-Yan Liu (IJCAI, 2021)

MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks. - Tianhao Zhang; Qiwei Ye; Jiang Bian 002; Guangming Xie; Tie-Yan Liu (IJCAI, 2021)

Independence-aware Advantage Estimation. - Pushi Zhang; Li Zhao 007; Guoqing Liu; Jiang Bian 002; Minlie Huang; Tao Qin 001; Tie-Yan Liu (IJCAI, 2021)

Adaptive Text to Speech for Spontaneous Style. - Yuzi Yan; Xu Tan 003; Bohan Li 003; Guangyan Zhang; Tao Qin 001; Sheng Zhao; Yuan Shen 001; Wei-Qiang Zhang; Tie-Yan Liu (Interspeech, 2021)

NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. - Jin Xu 010; Xu Tan 003; Renqian Luo; Kaitao Song; Jian Li 015; Tao Qin 001; Tie-Yan Liu (KDD, 2021)

UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost. - Zhen Wu 002; Lijun Wu 003; Qi Meng; Yingce Xia; Shufang Xie 003; Tao Qin 001; Xinyu Dai; Tie-Yan Liu (NAACL-HLT, 2021)

Speech-T: Transducer for Text to Speech and Beyond. - Jiawei Chen 008; Xu Tan 003; Yichong Leng; Jin Xu 010; Guihua Wen; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2021)

The Open Catalyst Challenge 2021: Competition Report. - Abhishek Das; Muhammed Shuaibi; Aini Palizhati; Siddharth Goyal; Aditya Grover; Adeesh Kolluru; Janice Lan; Ammar Rizvi; Anuroop Sriram; Brandon M. Wood; Devi Parikh; Zachary W. Ulissi; et al. (NeurIPS (Competition and Demos), 2021)

FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition. - Yichong Leng; Xu Tan 003; Linchen Zhu; Jin Xu 010; Renqian Luo; Linquan Liu; Tao Qin 001; Xiangyang Li 001; Edward Lin; Tie-Yan Liu (NeurIPS, 2021)

Stylized Dialogue Generation with Multi-Pass Dual Learning. - Jinpeng Li 003; Yingce Xia; Rui Yan 001; Hongda Sun 001; Dongyan Zhao 001; Tie-Yan Liu (NeurIPS, 2021)

R-Drop: Regularized Dropout for Neural Networks. - Xiaobo Liang; Lijun Wu 003; Juntao Li; Yue Wang 039; Qi Meng; Tao Qin 001; Wei Chen 034; Min Zhang 005; Tie-Yan Liu (NeurIPS, 2021)

Learning Causal Semantic Representation for Out-of-Distribution Prediction. - Chang Liu 030; Xinwei Sun 001; Jindong Wang 001; Haoyue Tang; Tao Li 040; Tao Qin 001; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2021)

On the Generative Utility of Cyclic Conditionals. - Chang Liu 030; Haoyue Tang; Tao Qin 001; Jintao Wang; Tie-Yan Liu (NeurIPS, 2021)

Curriculum Offline Imitating Learning. - Minghuan Liu; Hanye Zhao; Zhengyu Yang 002; Jian Shen 003; Weinan Zhang 001; Li Zhao 007; Tie-Yan Liu (NeurIPS, 2021)

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. - Shengjie Luo; Shanda Li; Tianle Cai; Di He 001; Dinglan Peng; Shuxin Zheng; Guolin Ke; Liwei Wang 001; Tie-Yan Liu (NeurIPS, 2021)

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. - Jongjin Park; Younggyo Seo; Chang Liu 030; Li Zhao 007; Tao Qin 001; Jinwoo Shin; Tie-Yan Liu (NeurIPS, 2021)

Recovering Latent Causal Factor for Generalization to Distributional Shifts. - Xinwei Sun 001; Botong Wu; Xiangyu Zheng; Chang Liu 030; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2021)

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. - Bohan Wang; Huishuai Zhang; Jieyu Zhang; Qi Meng; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2021)

Do Transformers Really Perform Badly for Graph Representation? - Chengxuan Ying; Tianle Cai; Shengjie Luo; Shuxin Zheng; Guolin Ke; Di He 001; Yanming Shen; Tie-Yan Liu (NeurIPS, 2021)

Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. - Pushi Zhang; Xiaoyu Chen; Li Zhao 007; Wei Xiong 015; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2021)

Co-evolution Transformer for Protein Contact Prediction. - He Zhang; Fusong Ju; Jianwei Zhu; Liang He 010; Bin Shao; Nanning Zheng 001; Tie-Yan Liu (NeurIPS, 2021)

Path-BN: Towards effective batch normalization in the Path Space for ReLU networks. - Xufang Luo; Qi Meng; Wei Chen 034; Yunhong Wang 001; Tie-Yan Liu (UAI, 2021)

REST: Relational Event-driven Stock Trend Forecasting. - Wentao Xu; Weiqing Liu; Chang Xu 008; Jiang Bian 002; Jian Yin 001; Tie-Yan Liu (WWW, 2021)

Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction. - Siyuan Liu 005; Tong Wang 014; Qijiang Xu; Bin Shao; Jian Yin 001; Tie-Yan Liu (BMC Bioinform., 2021)

Revisiting Language Encoding in Learning Multilingual Representations. - Shengjie Luo; Kaiyuan Gao; Shuxin Zheng; Guolin Ke; Di He 001; Liwei Wang 001; Tie-Yan Liu (CoRR, 2021)

Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder. - Shuqi Lu; Chenyan Xiong; Di He 001; Guolin Ke; Waleed Malik; Zhicheng Dou; Paul Bennett 001; Tie-Yan Liu; Arnold Overwijk (CoRR, 2021)

LazyFormer: Self Attention with Lazy Update. - Chengxuan Ying; Guolin Ke; Di He 001; Tie-Yan Liu (CoRR, 2021)

Learning Invariant Representations across Domains and Tasks. - Jindong Wang 001; Wenjie Feng 001; Chang Liu 030; Chaohui Yu; Mingxuan Du; Renjun Xu; Tao Qin 001; Tie-Yan Liu (CoRR, 2021)

Learning Structures for Deep Neural Networks. - Jinhui Yuan; Fei Pan; Chunting Zhou; Tao Qin 001; Tie-Yan Liu (CoRR, 2021)

Adversarial Training with Rectified Rejection. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CoRR, 2021)

Machine-Learning Non-Conservative Dynamics for New-Physics Detection. - Ziming Liu; Bohan Wang; Qi Meng; Wei Chen 034; Max Tegmark; Tie-Yan Liu (CoRR, 2021)

Do Transformers Really Perform Bad for Graph Representation? - Chengxuan Ying; Tianle Cai; Shengjie Luo; Shuxin Zheng; Guolin Ke; Di He 001; Yanming Shen; Tie-Yan Liu (CoRR, 2021)

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. - Sang-gil Lee; Heeseung Kim; Chaehun Shin; Xu Tan 003; Chang Liu 030; Qi Meng; Tao Qin 001; Wei Chen 034; Sungroh Yoon; Tie-Yan Liu (CoRR, 2021)

Dual-view Molecule Pre-training. - Jinhua Zhu 001; Yingce Xia; Tao Qin 001; Wengang Zhou 001; Houqiang Li; Tie-Yan Liu (CoRR, 2021)

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. - Yichi Zhou; Shihong Song; Huishuai Zhang; Jun Zhu 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

A Survey on Neural Speech Synthesis. - Xu Tan 003; Tao Qin 001; Frank K. Soong; Tie-Yan Liu (CoRR, 2021)

Causally Invariant Predictor with Shift-Robustness. - Xiangyu Zheng; Xinwei Sun 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style. - Yuzi Yan; Xu Tan 003; Bohan Li 003; Guangyan Zhang; Tao Qin 001; Sheng Zhao; Yuan Shen 001; Wei-Qiang Zhang; Tie-Yan Liu (CoRR, 2021)

Instance-wise Graph-based Framework for Multivariate Time Series Forecasting. - Wentao Xu; Weiqing Liu; Jiang Bian 002; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

Discovering Drug-Target Interaction Knowledge from Biomedical Literature. - Yutai Hou; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Yang Fan; Jinhua Zhu 001; Wanxiang Che; Tao Qin 001; Tie-Yan Liu (CoRR, 2021)

FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. - Yichong Leng; Xu Tan 003; Rui Wang 028; Linchen Zhu; Jin Xu 010; Linquan Liu; Tao Qin 001; Xiang-Yang Li 001; Edward Lin; Tie-Yan Liu (CoRR, 2021)

HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information. - Wentao Xu; Weiqing Liu; Lewen Wang; Yingce Xia; Jiang Bian 002; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. - Bohan Wang; Huishuai Zhang; Jieyu Zhang; Qi Meng; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Equivariant vector field network for many-body system modeling. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Bin Shao; Tie-Yan Liu (CoRR, 2021)

Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model. - Liang He 010; Shizhuo Zhang; Lijun Wu 003; Huanhuan Xia; Fusong Ju; He Zhang; Siyuan Liu 005; Yingce Xia; Jianwei Zhu; Pan Deng; Bin Shao; Tao Qin 001; et al. (CoRR, 2021)

Indiscriminate Poisoning Attacks Are Shortcuts. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

Curriculum Offline Imitation Learning. - Minghuan Liu; Hanye Zhao; Zhengyu Yang 002; Jian Shen 003; Weinan Zhang 001; Li Zhao 007; Tie-Yan Liu (CoRR, 2021)

KGE-CL: Contrastive Learning of Knowledge Graph Embeddings. - Wentao Xu; Zhiping Luo; Weiqing Liu; Jiang Bian 002; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

SHGNN: Structure-Aware Heterogeneous Graph Neural Network. - Wentao Xu; Yingce Xia; Weiqing Liu; Jiang Bian 002; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

Information retrieval: a view from the Chinese IR community. - Zhumin Chen; Xueqi Cheng; Shoubin Dong; Zhicheng Dou; Jiafeng Guo; Xuanjing Huang 001; Yanyan Lan; Chenliang Li; Ru Li; Tie-Yan Liu; Yiqun Liu 001; Jun Ma 001; et al. (Frontiers Comput. Sci., 2021)

Demonstration actor critic. - Guoqing Liu; Li Zhao 007; Pushi Zhang; Jiang Bian 002; Tao Qin 001; Nenghai Yu; Tie-Yan Liu (Neurocomputing, 2021)

Dual Learning: Theoretical Study and an Algorithmic Extension. - Zhibing Zhao; Yingce Xia; Tao Qin 001; Lirong Xia; Tie-Yan Liu (SN Comput. Sci., 2021)

SAMF: a self-adaptive protein modeling framework. - Wenze Ding; Qijiang Xu; Siyuan Liu 005; Tong Wang 014; Bin Shao; Haipeng Gong; Tie-Yan Liu (Bioinform., 2021)

Revisiting Over-Smoothness in Text to Speech. - Yi Ren 006; Xu Tan 003; Tao Qin 001; Zhou Zhao 001; Tie-Yan Liu (ACL (1), 2022)

ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation. - Chang Liu 076; Xu Tan 003; Chongyang Tao; Zhenxin Fu; Dongyan Zhao 001; Tie-Yan Liu; Rui Yan 001 (ACL (1), 2022)

Finding the Dominant Winning Ticket in Pre-Trained Language Models. - Zhuocheng Gong; Di He 001; Yelong Shen; Tie-Yan Liu; Weizhu Chen; Dongyan Zhao 001; Ji-Rong Wen; Rui Yan 001 (ACL (Findings), 2022)

Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. - Guoqing Liu; Mengzhang Cai; Li Zhao 007; Tao Qin 001; Adrian Brown; Jimmy Bischoff; Tie-Yan Liu (CoG, 2022)

KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings. - Zhiping Luo; Wentao Xu; Weiqing Liu; Jiang Bian 002; Jian Yin 001; Tie-Yan Liu (COLING, 2022)

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CVPR, 2022)

TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method. - Zeqian Ju; Peiling Lu; Xu Tan 003; Rui Wang 031; Chen Zhang 020; Songruoyao Wu; Kejun Zhang; Xiang-Yang Li 001; Tao Qin 001; Tie-Yan Liu (EMNLP, 2022)

Target-Side Input Augmentation for Sequence to Sequence Generation. - Shufang Xie 003; Ang Lv; Yingce Xia; Lijun Wu 003; Tao Qin 001; Tie-Yan Liu; Rui Yan 001 (ICLR, 2022)

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. - Wei Fan 010; Shun Zheng 001; Xiaohan Yi; Wei Cao 007; Yanjie Fu; Jiang Bian 002; Tie-Yan Liu (ICLR, 2022)

Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. - Jiawei Huang; Jinglin Chen; Li Zhao 007; Tao Qin 001; Nan Jiang 008; Tie-Yan Liu (ICLR, 2022)

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. - Sang-gil Lee; Heeseung Kim; Chaehun Shin; Xu Tan 003; Chang Liu 030; Qi Meng; Tao Qin 001; Wei Chen 034; Sungroh Yoon; Tie-Yan Liu (ICLR, 2022)

Gradient Information Matters in Policy Optimization by Back-propagating through Model. - Chongchong Li; Yue Wang 017; Wei Chen 034; Yuting Liu 002; Zhi-Ming Ma; Tie-Yan Liu (ICLR, 2022)

SE(3) Equivariant Graph Neural Networks with Complete Local Frames. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (ICML, 2022)

Supervised Off-Policy Ranking. - Yue Jin; Yue Zhang; Tao Qin 001; Xudong Zhang 001; Jian Yuan; Houqiang Li; Tie-Yan Liu (ICML, 2022)

Analyzing and Mitigating Interference in Neural Architecture Search. - Jin Xu 010; Xu Tan 003; Kaitao Song; Renqian Luo; Yichong Leng; Tao Qin 001; Tie-Yan Liu; Jian Li 015 (ICML, 2022)

AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios. - Yihan Wu; Xu Tan 003; Bohan Li 003; Lei He 005; Sheng Zhao; Ruihua Song; Tao Qin 001; Tie-Yan Liu (INTERSPEECH, 2022)

MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks. - Peiling Lu; Xu Tan 003; Botao Yu; Tao Qin 001; Sheng Zhao; Tie-Yan Liu (ISMIR, 2022)

Availability Attacks Create Shortcuts. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (KDD, 2022)

Unified 2D and 3D Pre-Training of Molecular Representations. - Jinhua Zhu 001; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Tao Qin 001; Wengang Zhou 001; Houqiang Li; Tie-Yan Liu (KDD, 2022)

ReLyMe: Improving Lyric-to-Melody Generation by Incorporating Lyric-Melody Relationships. - Chen Zhang 020; LuChin Chang; Songruoyao Wu; Xu Tan 003; Tao Qin 001; Tie-Yan Liu; Kejun Zhang (ACM Multimedia, 2022)

A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation. - Kexun Zhang; Rui Wang 028; Xu Tan 003; Junliang Guo; Yi Ren 006; Tao Qin 001; Tie-Yan Liu (NAACL-HLT, 2022)

An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. - Xiaoyu Chen; Xiangming Zhu 002; Yufeng Zheng; Pushi Zhang; Li Zhao 007; Wenxue Cheng; Peng Cheng 005; Yongqiang Xiong; Tao Qin 001; Jianyu Chen; Tie-Yan Liu (NeurIPS, 2022)

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. - Jiawei Huang; Li Zhao 007; Tao Qin 001; Wei Chen 034; Nan Jiang 008; Tie-Yan Liu (NeurIPS, 2022)

BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis. - Yichong Leng; Zehua Chen; Junliang Guo; Haohe Liu; Jiawei Chen 008; Xu Tan 003; Danilo P. Mandic; Lei He 005; Xiangyang Li 001; Tao Qin 001; Sheng Zhao; Tie-Yan Liu (NeurIPS, 2022)

Your Transformer May Not be as Powerful as You Expect. - Shengjie Luo; Shanda Li; Shuxin Zheng; Tie-Yan Liu; Liwei Wang 001; Di He 001 (NeurIPS, 2022)

Quantized Training of Gradient Boosting Decision Trees. - Yu Shi; Guolin Ke; Zhuoming Chen; Shuxin Zheng; Tie-Yan Liu (NeurIPS, 2022)

Does Momentum Change the Implicit Regularization on Separable Data? - Bohan Wang; Qi Meng; Huishuai Zhang; Ruoyu Sun 001; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (NeurIPS, 2022)

Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation. - Botao Yu; Peiling Lu; Rui Wang 028; Wei Hu; Xu Tan 003; Wei Ye 004; Shikun Zhang; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2022)

Improved drug-target interaction prediction with intermolecular graph transformer. - Siyuan Liu 005; Yusong Wang; Yifan Deng; Liang He 010; Bin Shao; Jian Yin 001; Nanning Zheng 001; Tie-Yan Liu; Tong Wang 014 (Briefings Bioinform., 2022)

SPRoBERTa: protein embedding learning with local fragment modeling. - Lijun Wu 003; Chengcan Yin; Jinhua Zhu 001; Zhen Wu 002; Liang He 010; Yingce Xia; Shufang Xie 003; Tao Qin 001; Tie-Yan Liu (Briefings Bioinform., 2022)

Direct Molecular Conformation Generation. - Jinhua Zhu 001; Yingce Xia; Chang Liu 030; Lijun Wu 003; Shufang Xie 003; Tong Wang 014; Yusong Wang; Wengang Zhou 001; Tao Qin 001; Houqiang Li; Tie-Yan Liu (CoRR, 2022)

AF2: Adaptive Focus Framework for Aerial Imagery Segmentation. - Lin Huang; Qiyuan Dong; Lijun Wu 003; Jia Zhang 004; Jiang Bian 002; Tie-Yan Liu (CoRR, 2022)

Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting. - Lin Huang; Lijun Wu 003; Jia Zhang 004; Jiang Bian 002; Tie-Yan Liu (CoRR, 2022)

Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. - Yu Shi; Shuxin Zheng; Guolin Ke; Yifei Shen; Jiacheng You; Jiyan He; Shengjie Luo; Chang Liu 030; Di He 001; Tie-Yan Liu (CoRR, 2022)

Multi-View Substructure Learning for Drug-Drug Interaction Prediction. - Zimeng Li; Shichao Zhu; Bin Shao; Tie-Yan Liu; Xiangxiang Zeng; Tong Wang 014 (CoRR, 2022)

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. - Peiyan Hu; Qi Meng; Bingguang Chen; Shiqi Gong; Yue Wang 017; Wei Chen 034; Rongchan Zhu; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2022)

METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. - Payal Bajaj; Chenyan Xiong; Guolin Ke; Xiaodong Liu 003; Di He 001; Saurabh Tiwary; Tie-Yan Liu; Paul Bennett 001; Xia Song; Jianfeng Gao 001 (CoRR, 2022)

Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent. - Da Yu; Gautam Kamath 001; Janardhan Kulkarni; Tie-Yan Liu; Jian Yin 001; Huishuai Zhang (CoRR, 2022)

LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. - Wenlei Shi; Xinquan Huang; Xiaotian Gao; Xinran Wei; Jia Zhang 004; Jiang Bian 002; Mao Yang 004; Tie-Yan Liu (CoRR, 2022)

Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations. - Rui Zhang 052; Peiyan Hu; Qi Meng; Yue Wang 017; Rongchan Zhu; Bingguang Chen; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2022)

SMT-DTA: Improving Drug-Target Affinity Prediction with Semi-supervised Multi-task Training. - Qizhi Pei; Lijun Wu 003; Jinhua Zhu 001; Yingce Xia; Shufang Xie 003; Tao Qin 001; Haiguang Liu; Tie-Yan Liu (CoRR, 2022)

Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. - Xiaodong Yang; Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (CoRR, 2022)

Provable Adaptivity in Adam. - Bohan Wang; Yushun Zhang; Huishuai Zhang; Qi Meng; Zhi-Ming Ma; Tie-Yan Liu; Wei Chen 034 (CoRR, 2022)

Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug Design. - Kehan Wu; Yingce Xia; Yang Fan; Pan Deng; Haiguang Liu; Lijun Wu 003; Shufang Xie 003; Tong Wang 014; Tao Qin 001; Tie-Yan Liu (CoRR, 2022)

Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-design. - Kaiyuan Gao; Lijun Wu 003; Jinhua Zhu 001; Tianbo Peng; Yingce Xia; Liang He 010; Shufang Xie 003; Tao Qin 001; Haiguang Liu; Kun He 001; Tie-Yan Liu (CoRR, 2022)

An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022. - Yusong Wang; Shaoning Li; Tong Wang 014; Zun Wang; Xinheng He; Bin Shao; Tie-Yan Liu (CoRR, 2022)

Stabilize deep ResNet with a sharp scaling factor τ. - Huishuai Zhang; Da Yu; Mingyang Yi; Wei Chen 034; Tie-Yan Liu (Mach. Learn., 2022)

Multi-Teacher Distillation With Single Model for Neural Machine Translation. - Xiaobo Liang; Lijun Wu 003; Juntao Li; Tao Qin 001; Min Zhang 005; Tie-Yan Liu (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Multimodal Sentiment Analysis With Two-Phase Multi-Task Learning. - Bo Yang; Lijun Wu 003; Jinhua Zhu 001; Bo Shao; Xiaola Lin; Tie-Yan Liu (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Neurally-Guided Semantic Navigation in Knowledge Graph. - Liang He 010; Bin Shao; Yanghua Xiao; Yatao Li; Tie-Yan Liu; Enhong Chen; Huanhuan Xia (IEEE Trans. Big Data, 2022)

Direct Molecular Conformation Generation. - Jinhua Zhu 001; Yingce Xia; Chang Liu 030; Lijun Wu 003; Shufang Xie 003; Yusong Wang; Tong Wang 014; Tao Qin 001; Wengang Zhou 001; Houqiang Li; Haiguang Liu; Tie-Yan Liu (Trans. Mach. Learn. Res., 2022)

BioGPT: generative pre-trained transformer for biomedical text generation and mining. - Renqian Luo; Liai Sun; Yingce Xia; Tao Qin 001; Sheng Zhang 012; Hoifung Poon; Tie-Yan Liu (Briefings Bioinform., 2022)

Discovering drug-target interaction knowledge from biomedical literature. - Yutai Hou; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Yang Fan; Jinhua Zhu 001; Tao Qin 001; Tie-Yan Liu (Bioinform., 2022)

Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations. - Shiqi Gong; Peiyan Hu; Qi Meng; Yue Wang 017; Rongchan Zhu; Bingguang Chen; Zhiming Ma; Hao Ni; Tie-Yan Liu (AAAI, 2023)

SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition. - Yichong Leng; Xu Tan 003; Wenjie Liu; Kaitao Song; Rui Wang 028; Xiang-Yang Li 001; Tao Qin 001; Edward Lin; Tie-Yan Liu (AAAI, 2023)

AMOM: Adaptive Masking over Masking for Conditional Masked Language Model. - Yisheng Xiao; Ruiyang Xu; Lijun Wu 003; Juntao Li; Tao Qin 001; Tie-Yan Liu; Min Zhang 005 (AAAI, 2023)

MolXPT: Wrapping Molecules with Text for Generative Pre-training. - Zequn Liu; Wei Zhang; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Tao Qin 001; Ming Zhang 004; Tie-Yan Liu (ACL (2), 2023)

Extract and Attend: Improving Entity Translation in Neural Machine Translation. - Zixin Zeng; Rui Wang 028; Yichong Leng; Junliang Guo; Shufang Xie 003; Xu Tan 003; Tao Qin 001; Tie-Yan Liu (ACL (Findings), 2023)

Learning Physics-Informed Neural Networks without Stacked Back-propagation. - Di He 001; Shanda Li; Wenlei Shi; Xiaotian Gao; Jia Zhang 004; Jiang Bian 002; Liwei Wang 001; Tie-Yan Liu (AISTATS, 2023)

De Novo Molecular Generation via Connection-aware Motif Mining. - Zijie Geng; Shufang Xie 003; Yingce Xia; Lijun Wu 003; Tao Qin 001; Jie Wang 005; Yongdong Zhang 001; Feng Wu 001; Tie-Yan Liu (ICLR, 2023)

One Transformer Can Understand Both 2D & 3D Molecular Data. - Shengjie Luo; Tianlang Chen; Yixian Xu; Shuxin Zheng; Tie-Yan Liu; Liwei Wang 001; Di He 001 (ICLR, 2023)

Making Better Decision by Directly Planning in Continuous Control. - Jinhua Zhu 001; Yue Wang 017; Lijun Wu 003; Tao Qin 001; Wengang Zhou 001; Tie-Yan Liu; Houqiang Li (ICLR, 2023)

𝒪-GNN: incorporating ring priors into molecular modeling. - Jinhua Zhu 001; Kehan Wu; Bohan Wang; Yingce Xia; Shufang Xie 003; Qi Meng; Lijun Wu 003; Tao Qin 001; Wengang Zhou 001; Houqiang Li; Tie-Yan Liu (ICLR, 2023)

NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition. - Xinquan Huang; Wenlei Shi; Qi Meng; Yue Wang 017; Xiaotian Gao; Jia Zhang 004; Tie-Yan Liu (ICML, 2023)

Retrosynthetic Planning with Dual Value Networks. - Guoqing Liu; Di Xue; Shufang Xie 003; Yingce Xia; Austin Tripp; Krzysztof Maziarz; Marwin H. S. Segler; Tao Qin 001; Zongzhang Zhang; Tie-Yan Liu (ICML, 2023)

Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. - Yuchen Fang; Zhenggang Tang; Kan Ren; Weiqing Liu; Li Zhao 007; Jiang Bian 002; Dongsheng Li 002; Weinan Zhang 001; Yong Yu 001; Tie-Yan Liu (KDD, 2023)

Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design. - Kaiyuan Gao; Lijun Wu 003; Jinhua Zhu 001; Tianbo Peng; Yingce Xia; Liang He 010; Shufang Xie 003; Tao Qin 001; Haiguang Liu; Kun He 001; Tie-Yan Liu (KDD, 2023)

Web-based Long-term Spine Treatment Outcome Forecasting. - Hangting Ye; Zhining Liu 002; Wei Cao 007; Amir M. Amiri; Jiang Bian 002; Yi Chang 001; Jon D. Lurie; Jim Weinstein; Tie-Yan Liu (KDD, 2023)

Dual-view Molecular Pre-training. - Jinhua Zhu 001; Yingce Xia; Lijun Wu 003; Shufang Xie 003; Wengang Zhou 001; Tao Qin 001; Houqiang Li; Tie-Yan Liu (KDD, 2023)

FABind: Fast and Accurate Protein-Ligand Binding. - Qizhi Pei; Kaiyuan Gao; Lijun Wu 003; Jinhua Zhu 001; Yingce Xia; Shufang Xie 003; Tao Qin 001; Kun He 001; Tie-Yan Liu; Rui Yan 001 (NeurIPS, 2023)

Geometric Transformer with Interatomic Positional Encoding. - Yusong Wang; Shaoning Li; Tong Wang 014; Bin Shao; Nanning Zheng 001; Tie-Yan Liu (NeurIPS, 2023)

Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. - Rui Zhang 052; Qi Meng; Rongchan Zhu; Yue Wang 017; Wenlei Shi; Shihua Zhang; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2023)

Extract and Attend: Improving Entity Translation in Neural Machine Translation. - Zixin Zeng; Rui Wang 028; Yichong Leng; Junliang Guo; Xu Tan 003; Tao Qin 001; Tie-Yan Liu (CoRR, 2023)

Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning. - Shuxin Zheng; Jiyan He; Chang Liu 030; Yu Shi; Ziheng Lu; Weitao Feng 001; Fusong Ju; Jiaxi Wang; Jianwei Zhu; Yaosen Min; He Zhang; Shidi Tang; et al. (CoRR, 2023)

Invertible Rescaling Network and Its Extensions. - Mingqing Xiao 002; Shuxin Zheng; Chang Liu 030; Zhouchen Lin; Tie-Yan Liu (Int. J. Comput. Vis., 2023)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent. - Da Yu; Gautam Kamath 001; Janardhan Kulkarni; Tie-Yan Liu; Jian Yin 001; Huishuai Zhang (Trans. Mach. Learn. Res., 2023)

DSN-DDI: an accurate and generalized framework for drug-drug interaction prediction by dual-view representation learning. - Zimeng Li; Shichao Zhu; Bin Shao; Xiangxiang Zeng; Tong Wang 014; Tie-Yan Liu (Briefings Bioinform., 2023)

R2-DDI: relation-aware feature refinement for drug-drug interaction prediction. - Jiacheng Lin; Lijun Wu 003; Jinhua Zhu 001; Xiaobo Liang; Yingce Xia; Shufang Xie 003; Tao Qin 001; Tie-Yan Liu (Briefings Bioinform., 2023)

Masked Contrastive Representation Learning for Reinforcement Learning. - Jinhua Zhu 001; Yingce Xia; Lijun Wu 003; Jiajun Deng; Wengang Zhou 001; Tao Qin 001; Tie-Yan Liu; Houqiang Li (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Incorporating NODE with pre-trained neural differential operator for learning dynamics. - Shiqi Gong; Qi Meng; Yue Wang 017; Lijun Wu 003; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (Neurocomputing, 2023)

Breaking the barriers of data scarcity in drug-target affinity prediction. - Qizhi Pei; Lijun Wu 003; Jinhua Zhu 001; Yingce Xia; Shufang Xie 003; Tao Qin 001; Haiguang Liu; Tie-Yan Liu; Rui Yan 001 (Briefings Bioinform., 2023)

A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond. - Yisheng Xiao; Lijun Wu 003; Junliang Guo; Juntao Li; Min Zhang 005; Tao Qin 001; Tie-Yan Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Regeneration Learning: A Learning Paradigm for Data Generation. - Xu Tan 003; Tao Qin 001; Jiang Bian 002; Tie-Yan Liu; Yoshua Bengio (AAAI, 2024)

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation. - Yunyang Li; Yusong Wang; Lin Huang; Han Yang; Xinran Wei; Jia Zhang 004; Tong Wang 014; Zun Wang; Bin Shao; Tie-Yan Liu (ICLR, 2024)

GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. - Tianlang Chen; Shengjie Luo; Di He 001; Shuxin Zheng; Tie-Yan Liu; Liwei Wang 001 (ICML, 2024)

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction. - He Zhang; Chang Liu 030; Zun Wang; Xinran Wei; Siyuan Liu 005; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (ICML, 2024)

Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation. - Ang Lv; Xu Tan 003; Tao Qin 001; Tie-Yan Liu; Rui Yan 001 (IJCAI, 2024)

Provable Adaptivity of Adam under Non-uniform Smoothness. - Bohan Wang; Yushun Zhang; Huishuai Zhang; Qi Meng; Ruoyu Sun 001; Zhi-Ming Ma; Tie-Yan Liu; Zhi-Quan Luo; Wei Chen 034 (KDD, 2024)

Bridging Geometric States via Geometric Diffusion Bridge. - Shengjie Luo; Yixian Xu; Di He 001; Shuxin Zheng; Tie-Yan Liu; Liwei Wang 001 (NeurIPS, 2024)

Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning. - Yuxuan Ren; Dihan Zheng; Chang Liu 030; Peiran Jin; Yu Shi; Lin Huang; Jiyan He; Shengjie Luo; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2024)

Self-Consistency Training for Hamiltonian Prediction. - He Zhang; Chang Liu 030; Zun Wang; Xinran Wei; Siyuan Liu 005; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (CoRR, 2024)

Pattern based learning and optimisation through pricing for bin packing problem. - Huayan Zhang; Ruibin Bai; Tie-Yan Liu; Jiawei Li 001; Bingchen Lin; Jianfeng Ren (CoRR, 2024)

SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation. - Liang He 010; Peiran Jin; Yaosen Min; Shufang Xie 003; Lijun Wu 003; Tao Qin 001; Xiaozhuan Liang; Kaiyuan Gao; Yuliang Jiang; Tie-Yan Liu (CoRR, 2024)

Predicting equilibrium distributions for molecular systems with deep learning. - Shuxin Zheng; Jiyan He; Chang Liu 030; Yu Shi; Ziheng Lu; Weitao Feng 001; Fusong Ju; Jiaxi Wang; Jianwei Zhu; Yaosen Min; He Zhang; Shidi Tang; et al. (Nat. Mac. Intell., 2024)

Author Correction: Predicting equilibrium distributions for molecular systems with deep learning. - Shuxin Zheng; Jiyan He; Chang Liu 030; Yu Shi; Ziheng Lu; Weitao Feng 001; Fusong Ju; Jiaxi Wang; Jianwei Zhu; Yaosen Min; He Zhang; Shidi Tang; et al. (Nat. Mac. Intell., 2024)

LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data. - Xinquan Huang; Wenlei Shi; Xiaotian Gao; Xinran Wei; Jia Zhang 004; Jiang Bian 002; Mao Yang 004; Tie-Yan Liu (Neural Networks, 2024)

Challenges of COVID-19 Case Forecasting in the US, 2020-2021. - Velma K. Lopez; Estee Y. Cramer; Robert Pagano; John M. Drake; Eamon B. O'Dea; Madeline Adee; Turgay Ayer; Jagpreet Chhatwal; Ozden O. Dalgic; Mary A. Ladd; Benjamin P. Linas; Peter P. Mueller; et al. (PLoS Comput. Biol., 2024)

NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality. - Xu Tan 003; Jiawei Chen 008; Haohe Liu; Jian Cong; Chen Zhang 020; Yanqing Liu; Xi Wang 016; Yichong Leng; Yuanhao Yi; Lei He 005; Sheng Zhao; Tao Qin 001; et al. (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Randomness Regularization With Simple Consistency Training for Neural Networks. - Juntao Li; Xiaobo Liang; Lijun Wu 003; Yue Wang 039; Qi Meng; Tao Qin 001; Min Zhang 005; Tie-Yan Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Digger-Guider: High-Frequency Factor Extraction for Stock Trend Prediction. - Yang Liu 278; Chang Xu 008; Min Hou; Weiqing Liu; Jiang Bian 002; Qi Liu 003; Tie-Yan Liu (IEEE Trans. Knowl. Data Eng., 2024)

NatureLM: Deciphering the Language of Nature for Scientific Discovery. - Yingce Xia; Peiran Jin; Shufang Xie 003; Liang He 010; Chuan Cao; Renqian Luo; Guoqing Liu; Yue Wang 017; Zequn Liu; Yuan-Jyue Chen; Zekun Guo; Yeqi Bai; et al. (CoRR, 2025)

Modeling Earth-Scale Human-Like Societies with One Billion Agents. - Haoxiang Guan; Jiyan He; Liyang Fan; Zhenzhen Ren 001; Shaobin He; Xin Yu; Yuan Chen; Shuxin Zheng; Tie-Yan Liu; Zhen Liu (CoRR, 2025)

Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. - Rui Zhang 052; Qi Meng; Rongchan Zhu; Yue Wang 017; Wenlei Shi; Shihua Zhang; Zhi-Ming Ma; Tie-Yan Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)