Re-lighting and Compensation for Face Images. - Xiaoyue Jiang; Tuo Zhao; Rong Xiao; Rongchun Zhao (CAIP, 2005)

Curve Mapping Based Illumination Adjustment for Face Detection. - Xiaoyue Jiang; Tuo Zhao; Rongchun Zhao (ACIVS, 2006)

Feature selection for linear support vector machines. - Zhizheng Liang; Tuo Zhao (ICPR (2), 2006)

A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition. - Tuo Zhao; Zhizheng Liang; David Zhang 001; Yahui Liu (ICB, 2007)

Interest filter vs. interest operator: Face recognition using Fisher linear discriminant based on interest filter representation. - Tuo Zhao; Zhizheng Liang; David Zhang 001; Quan Zou 001 (Pattern Recognit. Lett., 2008)

Predicting RNA secondary structure based on the class information and Hopfield network. - Quan Zou 001; Tuo Zhao; Yang Liu 006; Maozu Guo 001 (Comput. Biol. Medicine, 2009)

Projected gradient method for kernel discriminant nonnegative matrix factorization and the applications. - Zhizheng Liang; Youfu Li 001; Tuo Zhao (Signal Process., 2010)

Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation. - Tuo Zhao; Kathryn Roeder; Han Liu 001 (NIPS, 2012)

Sparse Additive Machine. - Tuo Zhao; Han Liu 001 (AISTATS, 2012)

The huge Package for High-dimensional Undirected Graph Estimation in R. - Tuo Zhao; Han Liu 001; Kathryn Roeder; John D. Lafferty; Larry A. Wasserman (J. Mach. Learn. Res., 2012)

Sparse Inverse Covariance Estimation with Calibration. - Tuo Zhao; Han Liu 001 (NIPS, 2013)

CODA: high dimensional copula discriminant analysis. - Fang Han; Tuo Zhao; Han Liu 001 (J. Mach. Learn. Res., 2013)

Multilevel sampling and aggregation for discriminative training. - Yunxin Zhao; Tuo Zhao; Xin Chen (ISCSLP, 2014)

Building an ensemble of CD-DNN-HMM acoustic model using random forests of phonetic decision trees. - Tuo Zhao; Yunxin Zhao; Xin Chen (ISCSLP, 2014)

Multivariate Regression with Calibration. - Han Liu 001; Lie Wang 002; Tuo Zhao (NIPS, 2014)

Accelerated Mini-batch Randomized Block Coordinate Descent Method. - Tuo Zhao; Mo Yu; Yiming Wang; Raman Arora; Han Liu 001 (NIPS, 2014)

Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory. - Tuo Zhao; Han Liu 001; Tong Zhang 001 (CoRR, 2014)

Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions. - Tuo Zhao; Han Liu 001 (IEEE Trans. Inf. Theory, 2014)

Time-frequency kernel-based CNN for speech recognition. - Tuo Zhao; Yunxin Zhao; Xin Chen (INTERSPEECH, 2015)

A Nonconvex Optimization Framework for Low Rank Matrix Estimation. - Tuo Zhao; Zhaoran Wang 001; Han Liu 001 (NIPS, 2015)

The flare package for high dimensional linear regression and precision matrix estimation in R. - Xingguo Li; Tuo Zhao; Xiaoming Yuan 001; Han Liu 001 (J. Mach. Learn. Res., 2015)

Calibrated multivariate regression with application to neural semantic basis discovery. - Han Liu 001; Lie Wang 002; Tuo Zhao (J. Mach. Learn. Res., 2015)

An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Mingyi Hong 001 (AISTATS, 2016)

Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Jarvis D. Haupt (ICML, 2016)

Subpixel mapping of hyperspectral images based on collaborative representation. - Xiaoqin Xue; Yifan Zhang 006; Tuo Zhao; Mingyi He (IGARSS, 2016)

Hyperspectral and multispectral image fusion using collaborative representation with local adaptive dictionary pair. - Tuo Zhao; Yifan Zhang 006; Xiaoqin Xue; Mingyi He (IGARSS, 2016)

NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. - Davood Hajinezhad; Mingyi Hong 001; Tuo Zhao; Zhaoran Wang 001 (NIPS, 2016)

A First Order Free Lunch for SQRT-Lasso. - Xingguo Li; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (CoRR, 2016)

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. - Xingguo Li; Zhaoran Wang 001; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Tuo Zhao (CoRR, 2016)

Ensemble Acoustic Modeling for CD-DNN-HMM Using Random Forests of Phonetic Decision Trees. - Tuo Zhao; Yunxin Zhao; Xin Chen (J. Signal Process. Syst., 2016)

Hyperspectral and multispectral image fusion using local spatial-spectral dictionary pair. - Yifan Zhang 006; Tuo Zhao; Mingyi He (APSIPA, 2017)

Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability. - Zhehui Chen; Lin F. Yang; Chris Junchi Li; Tuo Zhao (ICML, 2017)

The Opensesame NIST 2016 Speaker Recognition Evaluation System. - Gang Liu; Qi Qian 001; Zhibin Wang 004; Qingen Zhao; Tianzhou Wang; Hao Li 030; Jian Xue; Shenghuo Zhu; Rong Jin 001; Tuo Zhao (INTERSPEECH, 2017)

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning. - Xingguo Li; Lin Yang 011; Jason Ge; Jarvis D. Haupt; Tong Zhang 001; Tuo Zhao (NIPS, 2017)

Deep Hyperspherical Learning. - Weiyang Liu; Yan-Ming Zhang; Xingguo Li; Zhen Liu 019; Bo Dai 001; Tuo Zhao; Le Song (NIPS, 2017)

Parametric Simplex Method for Sparse Learning. - Haotian Pang; Han Liu 001; Robert J. Vanderbei; Tuo Zhao (NIPS, 2017)

Online Multiview Representation Learning: Dropping Convexity for Better Efficiency. - Zhehui Chen; Forest L. Yang; Chris Junchi Li; Tuo Zhao (CoRR, 2017)

On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions. - Xingguo Li; Lin F. Yang; Jason Ge; Jarvis D. Haupt; Tong Zhang 001; Tuo Zhao (CoRR, 2017)

Homotopy Parametric Simplex Method for Sparse Learning. - Haotian Pang; Tuo Zhao; Robert J. Vanderbei; Han Liu 001 (CoRR, 2017)

Dynamic Factorization and Partition of Complex Networks. - Lin F. Yang; Vladimir Braverman; Tuo Zhao; Mengdi Wang (CoRR, 2017)

Deep Hyperspherical Learning. - Weiyang Liu; Yan-Ming Zhang; Xingguo Li; Zhiding Yu; Bo Dai 001; Tuo Zhao; Le Song (CoRR, 2017)

Misspecified Nonconvex Statistical Optimization for Phase Retrieval. - Zhuoran Yang; Lin F. Yang; Ethan X. Fang; Tuo Zhao; Zhaoran Wang 001; Matey Neykov (CoRR, 2017)

Excavation equipment classification based on improved MFCC features and ELM. - Jiuwen Cao; Tuo Zhao; Jianzhong Wang; Ruirong Wang; Yun Chen (Neurocomputing, 2017)

On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Mingyi Hong 001 (J. Mach. Learn. Res., 2017)

An enhance excavation equipments classification algorithm based on acoustic spectrum dynamic feature. - Jiuwen Cao; Wuhao Huang; Tuo Zhao; Jianzhong Wang; Ruirong Wang (Multidimens. Syst. Signal Process., 2017)

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. - Minshuo Chen; Lin Yang 011; Mengdi Wang; Tuo Zhao (NeurIPS, 2018)

Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization. - Tianyi Liu; Shiyang Li; Jianping Shi; Enlu Zhou; Tuo Zhao (NeurIPS, 2018)

The Physical Systems Behind Optimization Algorithms. - Lin F. Yang; Raman Arora; Vladimir Braverman; Tuo Zhao (NeurIPS, 2018)

Provable Gaussian Embedding with One Observation. - Ming Yu 005; Zhuoran Yang; Tuo Zhao; Mladen Kolar; Zhaoran Wang 001 (NeurIPS, 2018)

Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations. - Tianyi Liu; Zhehui Chen; Enlu Zhou; Tuo Zhao (CoRR, 2018)

Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models. - Yingxiang Yang; Adams Wei Yu; Zhaoran Wang 001; Tuo Zhao (CoRR, 2018)

On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization. - Zhehui Chen; Xingguo Li; Lin F. Yang; Jarvis D. Haupt; Tuo Zhao (CoRR, 2018)

On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond. - Xingguo Li; Junwei Lu; Zhaoran Wang 001; Jarvis D. Haupt; Tuo Zhao (CoRR, 2018)

Learning to Defense by Learning to Attack. - Zhehui Chen; Haoming Jiang; Bo Dai 001; Tuo Zhao (CoRR, 2018)

On Computation and Generalization of GANs with Spectrum Control. - Haoming Jiang; Zhehui Chen; Minshuo Chen; Feng Liu; Dingding Wang 001; Tuo Zhao (CoRR, 2018)

On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. - Zhehui Chen; Xingguo Li; Lin Yang 011; Jarvis D. Haupt; Tuo Zhao (AISTATS, 2019)

Learning to Defense by Learning to Attack. - Zhehui Chen; Haoming Jiang; Yuyang Shi 001; Bo Dai 001; Tuo Zhao (DGS@ICLR, 2019)

On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. - Haoming Jiang; Zhehui Chen; Minshuo Chen; Feng Liu; Dingding Wang 001; Tuo Zhao (ICLR (Poster), 2019)

On Scalable and Efficient Computation of Large Scale Optimal Transport. - Yujia Xie; Minshuo Chen; Haoming Jiang; Tuo Zhao; Hongyuan Zha (ICML, 2019)

Toward Understanding the Importance of Noise in Training Neural Networks. - Mo Zhou; Tianyi Liu; Yan Li 074; Dachao Lin; Enlu Zhou; Tuo Zhao (ICML, 2019)

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. - Minshuo Chen; Haoming Jiang; Wenjing Liao; Tuo Zhao (NeurIPS, 2019)

Towards Understanding the Importance of Shortcut Connections in Residual Networks. - Tianyi Liu; Minshuo Chen; Mo Zhou; Simon S. Du; Enlu Zhou; Tuo Zhao (NeurIPS, 2019)

Meta Learning with Relational Information for Short Sequences. - Yujia Xie; Haoming Jiang; Feng Liu; Tuo Zhao; Hongyuan Zha (NeurIPS, 2019)

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. - Xingguo Li; Haoming Jiang; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (UAI, 2019)

Online Factorization and Partition of Complex Networks by Random Walk. - Lin F. Yang; Zheng Yu; Vladimir Braverman; Tuo Zhao; Mengdi Wang (UAI, 2019)

Review wearable sensing system for gait recognition. - Gelan Yang; Wei Tan; Huixia Jin; Tuo Zhao; Li Tu (Clust. Comput., 2019)

Inductive Bias of Gradient Descent based Adversarial Training on Separable Data. - Yan Li 074; Ethan X. Fang; Huan Xu; Tuo Zhao (CoRR, 2019)

Towards Understanding the Importance of Noise in Training Neural Networks. - Mo Zhou; Tianyi Liu; Yan Li 074; Dachao Lin; Enlu Zhou; Tuo Zhao (CoRR, 2019)

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. - Jason Ge; Xingguo Li; Haoming Jiang; Han Liu 001; Tong Zhang 001; Mengdi Wang; Tuo Zhao (J. Mach. Learn. Res., 2019)

Misspecified nonconvex statistical optimization for sparse phase retrieval. - Zhuoran Yang; Lin F. Yang; Ethan X. Fang; Tuo Zhao; Zhaoran Wang 001; Matey Neykov (Math. Program., 2019)

Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. - Xingguo Li; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Zhaoran Wang 001; Tuo Zhao (IEEE Trans. Inf. Theory, 2019)

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. - Haoming Jiang; Pengcheng He; Weizhu Chen; Xiaodong Liu 003; Jianfeng Gao 001; Tuo Zhao (ACL, 2020)

Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. - Haoming Jiang; Chen Liang 006; Chong Wang; Tuo Zhao (ACL, 2020)

On Generalization Bounds of a Family of Recurrent Neural Networks. - Minshuo Chen; Xingguo Li; Tuo Zhao (AISTATS, 2020)

Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. - Lingkai Kong; Haoming Jiang; Yuchen Zhuang; Jie Lyu 005; Tuo Zhao; Chao Zhang 014 (EMNLP (1), 2020)

On Computation and Generalization of Generative Adversarial Imitation Learning. - Minshuo Chen; Yizhou Wang 006; Tianyi Liu; Zhuoran Yang; Xingguo Li; Zhaoran Wang 001; Tuo Zhao (ICLR, 2020)

Implicit Bias of Gradient Descent based Adversarial Training on Separable Data. - Yan Li 074; Ethan X. Fang; Huan Xu; Tuo Zhao (ICLR, 2020)

Deep Reinforcement Learning with Robust and Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (ICML, 2020)

Transformer Hawkes Process. - Simiao Zuo; Haoming Jiang; Zichong Li; Tuo Zhao; Hongyuan Zha (ICML, 2020)

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. - Chen Liang 006; Yue Yu 001; Haoming Jiang; Siawpeng Er; Ruijia Wang; Tuo Zhao; Chao Zhang 014 (KDD, 2020)

Towards Understanding Hierarchical Learning: Benefits of Neural Representations. - Minshuo Chen; Yu Bai 017; Jason D. Lee; Tuo Zhao; Huan Wang 014; Caiming Xiong; Richard Socher (NeurIPS, 2020)

Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective. - Kaixuan Huang; Yuqing Wang; Molei Tao; Tuo Zhao (NeurIPS, 2020)

Differentiable Top-k with Optimal Transport. - Yujia Xie; Hanjun Dai; Minshuo Chen; Bo Dai 001; Tuo Zhao; Hongyuan Zha; Wei Wei 019; Tomas Pfister (NeurIPS, 2020)

The Role of Mobile Social Application in Stimulating Learning Stickiness in Blended Learning. - Lin Zhang; Zhen Shao; Tuo Zhao; Susan A. Brown (PACIS, 2020)

Spatial Resolution Enhancement of Remote Sensing Hyperspectral Images With Localized Spatial-Spectral Dictionary Pair. - Yifan Zhang 006; Jin Tian; Tuo Zhao; Shaohui Mei (IEEE Access, 2020)

Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation. - Minshuo Chen; Wenjing Liao; Hongyuan Zha; Tuo Zhao (CoRR, 2020)

Differentiable Top-k Operator with Optimal Transport. - Yujia Xie; Hanjun Dai; Minshuo Chen; Bo Dai 001; Tuo Zhao; Hongyuan Zha; Wei Wei 019; Tomas Pfister (CoRR, 2020)

Deep Reinforcement Learning with Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (CoRR, 2020)

Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers. - David Joseph Munzer; Siawpeng Er; Minshuo Chen; Yan Li 074; Naga Sasikanth Mannem; Tuo Zhao; Hua Wang 006 (CoRR, 2020)

Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks. - Minshuo Chen; Hao Liu 028; Wenjing Liao; Tuo Zhao (CoRR, 2020)

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. - Haoming Jiang; Danqing Zhang; Tianyu Cao 001; Bing Yin; Tuo Zhao (ACL/IJCNLP (1), 2021)

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. - Chen Liang 006; Simiao Zuo; Minshuo Chen; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Tuo Zhao; Weizhu Chen (ACL/IJCNLP (1), 2021)

Learning to Defend by Learning to Attack. - Haoming Jiang; Zhehui Chen; Yuyang Shi 001; Bo Dai 001; Tuo Zhao (AISTATS, 2021)

Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. - Tianyi Liu; Yan Li 074; Song Wei; Enlu Zhou; Tuo Zhao (AISTATS, 2021)

QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction. - Danqing Zhang; Zheng Li 018; Tianyu Cao 001; Chen Luo 003; Tony Wu; Hanqing Lu; Yiwei Song; Bing Yin; Tuo Zhao; Qiang Yang 001 (CIKM, 2021)

Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. - Haoming Jiang; Bo Dai 001; Mengjiao Yang 001; Tuo Zhao; Wei Wei 019 (EMNLP (1), 2021)

Token-wise Curriculum Learning for Neural Machine Translation. - Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Weizhu Chen; Jianfeng Gao 001; Tuo Zhao (EMNLP (Findings), 2021)

ARCH: Efficient Adversarial Regularized Training with Caching. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (EMNLP (Findings), 2021)

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (EMNLP (1), 2021)

A Hypergradient Approach to Robust Regression without Correspondence. - Yujia Xie; Yixiu Mao; Simiao Zuo; Hongteng Xu; Xiaojing Ye; Tuo Zhao; Hongyuan Zha (ICLR, 2021)

How Important is the Train-Validation Split in Meta-Learning? - Yu Bai 017; Minshuo Chen; Pan Zhou 002; Tuo Zhao; Jason D. Lee; Sham M. Kakade; Huan Wang 014; Caiming Xiong (ICML, 2021)

Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. - Hao Liu 028; Minshuo Chen; Tuo Zhao; Wenjing Liao (ICML, 2021)

UNet++-Based Multi-Channel Speech Dereverberation and Distant Speech Recognition. - Tuo Zhao; Yunxin Zhao; Shaojun Wang; Mei Han (ISCSLP, 2021)

Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. - Yue Yu 001; Simiao Zuo; Haoming Jiang; Wendi Ren; Tuo Zhao; Chao Zhang 014 (NAACL-HLT, 2021)

Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. - Minshuo Chen; Yan Li 074; Ethan Wang; Zhuoran Yang; Zhaoran Wang 001; Tuo Zhao (NeurIPS, 2021)

Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (CoRR, 2021)

COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction. - Siawpeng Er; Shihao Yang 002; Tuo Zhao (CoRR, 2021)

Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. - Yan Li 074; Lingxiao Wang 003; Jiachen Yang; Ethan Wang; Zhaoran Wang 001; Tuo Zhao; Hongyuan Zha (CoRR, 2021)

Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data. - Yan Li 074; Caleb Ju; Ethan X. Fang; Tuo Zhao (CoRR, 2021)

Learning Generalizable Vision-Tactile Robotic Grasping Strategy for Deformable Objects via Transformer. - Yunhai Han; Rahul Batra; Nathan Boyd; Tuo Zhao; Yu She; Seth Hutchinson 001; Ye Zhao 002 (CoRR, 2021)

Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval. - Lewis Liu; Songtao Lu; Tuo Zhao; Zhaoran Wang 001 (IEEE Trans. Signal Process., 2021)

CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. - Chen Liang 006; Pengcheng He; Yelong Shen; Weizhu Chen; Tuo Zhao (ACL (1), 2022)

Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. - Tianyi Liu; Yan Li 074; Enlu Zhou; Tuo Zhao (AISTATS, 2022)

Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. - Jiachen Yang; Ethan Wang; Rakshit Trivedi; Tuo Zhao; Hongyuan Zha (AAMAS, 2022)

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. - Yan Li 074; Dhruv Choudhary; Xiaohan Wei; Baichuan Yuan; Bhargav Bhushanam; Tuo Zhao; Guanghui Lan (ICLR, 2022)

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. - Chen Liang 006; Haoming Jiang; Simiao Zuo; Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (ICLR, 2022)

Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. - Yuqing Wang; Minshuo Chen; Tuo Zhao; Molei Tao (ICLR, 2022)

Taming Sparsely Activated Transformer with Stochastic Experts. - Simiao Zuo; Xiaodong Liu 003; Jian Jiao 007; Young Jin Kim 001; Hany Hassan; Ruofei Zhang; Jianfeng Gao 001; Tuo Zhao (ICLR, 2022)

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. - Hao Liu 028; Minshuo Chen; Siawpeng Er; Wenjing Liao; Tong Zhang 001; Tuo Zhao (ICML, 2022)

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. - Qingru Zhang; Simiao Zuo; Chen Liang 006; Alexander Bukharin; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2022)

Steering vector correction in MVDR beamformer for speech enhancement. - Suliang Bu; Yunxin Zhao; Tuo Zhao (INTERSPEECH, 2022)

Adversarially Regularized Policy Learning Guided by Trajectory Optimization. - Zhigen Zhao; Simiao Zuo; Tuo Zhao; Ye Zhao 002 (L4DC, 2022)

CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. - Rui Feng; Chen Luo 003; Qingyu Yin; Bing Yin; Tuo Zhao; Chao Zhang 014 (NAACL-HLT, 2022)

Self-Training with Differentiable Teacher. - Simiao Zuo; Yue Yu 001; Chen Liang 006; Haoming Jiang; Siawpeng Er; Chao Zhang 014; Tuo Zhao; Hongyuan Zha (NAACL-HLT (Findings), 2022)

MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. - Simiao Zuo; Qingru Zhang; Chen Liang 006; Pengcheng He; Tuo Zhao; Weizhu Chen (NAACL-HLT, 2022)

On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. - Biraj Dahal; Alexander Havrilla; Minshuo Chen; Tuo Zhao; Wenjing Liao (NeurIPS, 2022)

TDOA Estimation of Speech Source in Noisy Reverberant Environments. - Suliang Bu; Tuo Zhao; Yunxin Zhao (SLT, 2022)

Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network. - Siawpeng Er; Edward Liu; Minshuo Chen; Yan Li 074; Yuqi Liu; Tuo Zhao; Hua Wang 006 (CoRR, 2022)

Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. - Yan Li 074; Tuo Zhao; Guanghui Lan (CoRR, 2022)

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks. - Jie Wang 049; Minshuo Chen; Tuo Zhao; Wenjing Liao; Yao Xie 002 (CoRR, 2022)

Differentially Private Estimation of Hawkes Process. - Simiao Zuo; Tianyi Liu; Tuo Zhao; Hongyuan Zha (CoRR, 2022)

DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. - Simiao Zuo; Haoming Jiang; Qingyu Yin; Xianfeng Tang; Bing Yin; Tuo Zhao (CoRR, 2022)

First-order Policy Optimization for Robust Markov Decision Process. - Yan Li 074; Tuo Zhao; Guanghui Lan (CoRR, 2022)

High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. - Jiahui Cheng; Minshuo Chen; Hao Liu 028; Tuo Zhao; Wenjing Liao (CoRR, 2022)

Efficient Long Sequence Modeling via State Space Augmented Transformer. - Simiao Zuo; Xiaodong Liu 003; Jian Jiao 007; Denis Charles; Eren Manavoglu; Tuo Zhao; Jianfeng Gao 001 (CoRR, 2022)

Understanding users' trust transfer mechanism in a blockchain-enabled platform: A mixed methods study. - Zhen Shao; Lin Zhang; Susan A. Brown; Tuo Zhao (Decis. Support Syst., 2022)

Modeling Speech Structure to Improve T-F Masks for Speech Enhancement and Recognition. - Suliang Bu; Yunxin Zhao; Tuo Zhao; Shaojun Wang; Mei Han (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. - Simiao Zuo; Qingyu Yin; Haoming Jiang; Shaohui Xi; Bing Yin; Chao Zhang 014; Tuo Zhao (ACL (industry), 2023)

Reinforcement Learning for Adaptive Mesh Refinement. - Jiachen Yang; Tarik Dzanic; Brenden K. Petersen; Jun Kudo; Ketan Mittal; Vladimir Z. Tomov; Jean-Sylvain Camier; Tuo Zhao; Hongyuan Zha; Tzanio V. Kolev; Robert W. Anderson; Daniel M. Faissol (AISTATS, 2023)

HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference. - Haoyu Wang 004; Yaqing Wang 001; Tianci Liu 003; Tuo Zhao; Jing Gao 004 (EMNLP (Findings), 2023)

Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. - Qingru Zhang; Dhananjay Ram; Cole Hawkins; Sheng Zha; Tuo Zhao (EMNLP (Findings), 2023)

Joint Estimation of DOA and Distance in Noisy Reverberant Conditions. - Suliang Bu; Tuo Zhao; Yunxin Zhao (ICASSP, 2023)

Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. - Xiang Ji; Minshuo Chen; Mengdi Wang; Tuo Zhao (ICLR, 2023)

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. - Chen Liang 006; Haoming Jiang; Zheng Li 018; Xianfeng Tang; Bing Yin; Tuo Zhao (ICLR, 2023)

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. - Qingru Zhang; Minshuo Chen; Alexander Bukharin; Pengcheng He; Yu Cheng 001; Weizhu Chen; Tuo Zhao (ICLR, 2023)

Machine Learning Force Fields with Data Cost Aware Training. - Alexander Bukharin; Tianyi Liu; Shengjie Wang; Simiao Zuo; Weihao Gao; Wen Yan; Tuo Zhao (ICML, 2023)

Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. - Minshuo Chen; Kaixuan Huang; Tuo Zhao; Mengdi Wang (ICML, 2023)

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. - Zichong Li; Yanbo Xu; Simiao Zuo; Haoming Jiang; Chao Zhang; Tuo Zhao; Hongyuan Zha (ICML, 2023)

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. - Yixiao Li; Yifan Yu 008; Qingru Zhang; Chen Liang 006; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2023)

Less is More: Task-aware Layer-wise Distillation for Language Model Compression. - Chen Liang 006; Simiao Zuo; Qingru Zhang; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2023)

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. - Zixuan Zhang; Minshuo Chen; Mengdi Wang; Wenjing Liao; Tuo Zhao (ICML, 2023)

LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. - Haoyu Wang 004; Ruirui Li 002; Haoming Jiang; Zhengyang Wang; Xianfeng Tang; Bin Bi; Monica Xiao Cheng; Bing Yin; Yaqing Wang 001; Tuo Zhao; Jing Gao 004 (KDD, 2023)

Module-wise Adaptive Distillation for Multimodality Foundation Models. - Chen Liang 006; Jiahui Yu; Ming-Hsuan Yang 001; Matthew Brown 001; Yin Cui; Tuo Zhao; Boqing Gong; Tianyi Zhou 002 (NeurIPS, 2023)

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. - Alexander Bukharin; Yan Li; Yue Yu 001; Qingru Zhang; Zhehui Chen; Simiao Zuo; Chao Zhang 014; Songan Zhang; Tuo Zhao (NeurIPS, 2023)

Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. - Shenao Zhang; Boyi Liu 001; Zhaoran Wang 001; Tuo Zhao (NeurIPS, 2023)

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. - Chen Liang 006; Haoming Jiang; Zheng Li 018; Xianfeng Tang; Bin Yin; Tuo Zhao (CoRR, 2023)

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. - Kaiqi Zhang 002; Zixuan Zhang; Minshuo Chen; Mengdi Wang; Tuo Zhao; Yu-Xiang Wang 003 (CoRR, 2023)

Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems. - Xiang Ji; Huazheng Wang; Minshuo Chen; Tuo Zhao; Mengdi Wang (CoRR, 2023)

Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. - Alexander Bukharin; Yixiao Li; Pengcheng He; Weizhu Chen; Tuo Zhao (CoRR, 2023)

Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification. - Zichong Li; Qunzhi Xu; Zhenghao Xu; Yajun Mei; Tuo Zhao; Hongyuan Zha (CoRR, 2023)

Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. - Yuqing Wang; Zhenghao Xu; Tuo Zhao; Molei Tao (CoRR, 2023)

Data Diversity Matters for Robust Instruction Tuning. - Alexander Bukharin; Tuo Zhao (CoRR, 2023)

Pivotal Estimation of Linear Discriminant Analysis in High Dimensions. - Ethan X. Fang; Yajun Mei; Yuyang Shi; Qunzhi Xu; Tuo Zhao (J. Mach. Learn. Res., 2023)

Block Policy Mirror Descent. - Guanghui Lan; Yan Li 074; Tuo Zhao (SIAM J. Optim., 2023)

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. - Haoyu Wang 004; Tianci Liu 003; Ruirui Li 002; Monica Xiao Cheng; Tuo Zhao; Jing Gao 004 (EMNLP, 2024)

Data Diversity Matters for Robust Instruction Tuning. - Alexander Bukharin; Shiyang Li; Zhengyang Wang; Jingfeng Yang 001; Bing Yin; Xian Li; Chao Zhang 014; Tuo Zhao; Haoming Jiang (EMNLP (Findings), 2024)

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. - Haoyu Wang 004; Ruirui Li 002; Haoming Jiang; Jinjin Tian; Zhengyang Wang; Chen Luo 003; Xianfeng Tang; Monica Xiao Cheng; Tuo Zhao; Jing Gao 004 (EMNLP, 2024)

GEAR: An Efficient Error Reduction Framework for KV Cache Compression in LLM Inference. - Hao Kang; Qingru Zhang; Souvik Kundu 009; Geonhwa Jeong; Zaoxing Liu; Tushar Krishna; Tuo Zhao (ENLSP, 2024)

Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction. - Tuo Zhao; Xinxue Wang; Tingting Zhao 001; Yuan Wang 021; Yarui Chen; Jucheng Yang 001 (ICIC (LNAI 5), 2024)

LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models. - Yixiao Li; Yifan Yu 008; Chen Liang 006; Nikos Karampatziakis; Pengcheng He; Weizhu Chen; Tuo Zhao (ICLR, 2024)

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. - Qingru Zhang; Chandan Singh; Liyuan Liu; Xiaodong Liu 003; Bin Yu 001; Jianfeng Gao 001; Tuo Zhao (ICLR, 2024)

Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process. - Zichong Li; Qunzhi Xu; Zhenghao Xu; Yajun Mei; Tuo Zhao; Hongyuan Zha (ICML, 2024)

To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. - Zi-Hao Qiu; Siqi Guo 003; Mao Xu; Tuo Zhao; Lijun Zhang 005; Tianbao Yang (ICML, 2024)

A Cloud-Edge Intelligent Collaborative Framework and Its Applications in AIGC and Digital Twins. - Haiteng Wang; Lu Jiao; Tuo Zhao; Lei Ren 001 (IECON, 2024)

Robust Reinforcement Learning from Corrupted Human Feedback. - Alexander Bukharin; Ilgee Hong; Haoming Jiang; Zichong Li; Qingru Zhang; Zixuan Zhang; Tuo Zhao (NeurIPS, 2024)

Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. - Ilgee Hong; Zichong Li; Alexander Bukharin; Yixiao Li; Haoming Jiang; Tianbao Yang; Tuo Zhao (NeurIPS, 2024)

Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks. - Zhenghao Xu; Yuqing Wang; Tuo Zhao; Rachel Ward; Molei Tao (NeurIPS, 2024)

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. - Zixuan Zhang; Kaiqi Zhang 002; Minshuo Chen; Yuma Takeda; Mengdi Wang; Tuo Zhao; Yu-Xiang Wang 003 (NeurIPS, 2024)

Trust in Digital Commerce: the Moderating Effect of Blockchain Teability Labels. - Zhen Shao; Tuo Zhao; Lin Zhang; Yu Liu (PACIS, 2024)

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. - Haoyu Wang; Tuo Zhao; Jing Gao (CoRR, 2024)

GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. - Hao Kang; Qingru Zhang; Souvik Kundu 009; Geonhwa Jeong; Zaoxing Liu; Tushar Krishna; Tuo Zhao (CoRR, 2024)

Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach. - Hoang Huy Nguyen; Yan Li; Tuo Zhao (CoRR, 2024)

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. - Haoyu Wang 004; Tianci Liu 003; Tuo Zhao; Jing Gao 004 (CoRR, 2024)

Robust Reinforcement Learning from Corrupted Human Feedback. - Alexander Bukharin; Ilgee Hong; Haoming Jiang; Qingru Zhang; Zixuan Zhang; Tuo Zhao (CoRR, 2024)

Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering. - Qingru Zhang; Xiaodong Yu 003; Chandan Singh; Xiaodong Liu 003; Liyuan Liu; Jianfeng Gao 001; Tuo Zhao; Dan Roth 001; Hao Cheng 002 (CoRR, 2024)

RNR: Teaching Large Language Models to Follow Roles and Rules. - Kuan Wang; Alexander Bukharin; Haoming Jiang; Qingyu Yin; Zhengyang Wang; Tuo Zhao; Jingbo Shang; Chao Zhang 014; Bing Yin; Xian Li; Jianshu Chen; Shiyang Li (CoRR, 2024)

Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks. - Zhenghao Xu; Yuqing Wang; Tuo Zhao; Rachel Ward; Molei Tao (CoRR, 2024)

Digitally-enabled antecedents of trust, repurchase intention and the impact of blockchain traceability labels. - Lin Zhang; Zhen Shao; Tuo Zhao; Xiaotong Li; Jianfeng Zhang (Electron. Commer. Res. Appl., 2024)

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. - Hao Liu 028; Haizhao Yang; Minshuo Chen; Tuo Zhao; Wenjing Liao (J. Mach. Learn. Res., 2024)

Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. - Zhenghao Xu; Xiang Ji; Minshuo Chen; Mengdi Wang; Tuo Zhao (J. Mach. Learn. Res., 2024)

Learning explainable task-relevant state representation for model-free deep reinforcement learning. - Tingting Zhao 001; Guixi Li; Tuo Zhao; Yarui Chen; Ning Xie 003; Gang Niu 001; Masashi Sugiyama (Neural Networks, 2024)

Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. - Yan Li 074; Guanghui Lan; Tuo Zhao (Math. Program., 2024)

RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization. - Tianci Liu 003; Haoxiang Jiang; Tianze Wang; Ran Xu; Yue Yu; Linjun Zhang; Tuo Zhao; Haoyu Wang 004 (ACL (Findings), 2025)

MS-RainMamba: Learning Multi-Scale State Space Models for Single Image Deraining. - Haibo Li; Zhanshuo Liu; Tuo Zhao; Tingting Zhao 001; Yarui Chen; Ning Xie 003 (ICASSP, 2025)

The influences of four dimensions of perceived fit on individuals' utilisation of SPOCs: an extension of the task-technology fit model. - Lin Zhang; Zhen Shao; Tuo Zhao; Kuanchin Chen (Behav. Inf. Technol., 2025)

COSMOS: A Hybrid Adaptive Optimizer for Memory-Efficient Training of LLMs. - Liming Liu; Zhenghao Xu; Zixuan Zhang; Hao Kang; Zichong Li; Chen Liang; Weizhu Chen; Tuo Zhao (CoRR, 2025)

Discriminative Finetuning of Generative Large Language Models without Reward Models and Preference Data. - Siqi Guo 003; Ilgee Hong; Vicente Balmaseda; Tuo Zhao; Tianbao Yang (CoRR, 2025)

A Minimalist Example of Edge-of-Stability and Progressive Sharpening. - Liming Liu; Zixuan Zhang; Simon S. Du; Tuo Zhao (CoRR, 2025)

LLMs Can Generate a Better Answer by Aggregating Their Own Responses. - Zichong Li; Xinyu Feng; Yuheng Cai; Zixuan Zhang; Tianyi Liu; Chen Liang; Weizhu Chen; Haoyu Wang; Tuo Zhao (CoRR, 2025)

IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining. - Yixiao Li; Xianzhi Du; Ajay Jaiswal; Tao Lei; Tuo Zhao; Chong Wang; Jianyu Wang (CoRR, 2025)

Adversarial Training of Reward Models. - Alexander Bukharin; Haifeng Qian; Shengyang Sun; Adithya Renduchintala; Soumye Singhal; Zhilin Wang; Oleksii Kuchaiev; Olivier Delalleau; Tuo Zhao (CoRR, 2025)

NoWag: A Unified Framework for Shape Preserving Compression of Large Language Models. - Lawrence Liu; Inesh Chakrabarti; Yixiao Li; Mengdi Wang; Tuo Zhao; Lin F. Yang (CoRR, 2025)

Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models. - Ilgee Hong; Changlong Yu; Liang Qiu; Weixiang Yan; Zhenghao Xu; Haoming Jiang; Qingru Zhang; Qin Lu; Xin Liu; Chao Zhang; Tuo Zhao (CoRR, 2025)

SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation. - Zichong Li; Chen Liang 006; Zixuan Zhang; Ilgee Hong; Young Jin Kim 001; Weizhu Chen; Tuo Zhao (CoRR, 2025)

FDformer: A Fuzzy Dynamic Transformer-Based Network for Efficient Industrial Time Series Prediction. - Lei Ren 001; Tuo Zhao; Haiteng Wang (IEEE Trans. Fuzzy Syst., 2025)