Bo Dai

According to our database, Bo Dai authored at least 124 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models.

Haotian Sun, Yuchen Zhuang, Wei Wei, Chao Zhang, Bo Dai

CoRR, 2024

Beyond Expectations: Learning with Stochastic Dominance Made Practical.

Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai

CoRR, 2024

2023

Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning.

Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai

CoRR, 2023

DF2: Distribution-Free Decision-Focused Learning.

Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang

CoRR, 2023

Probabilistic Adaptation of Text-to-Video Models.

Mengjiao Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B. Tenenbaum, Pieter Abbeel

CoRR, 2023

AdaPlanner: Adaptive Planning from Feedback with Language Models.

Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang

CoRR, 2023

Learning Universal Policies via Text-Guided Video Generation.

Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel

CoRR, 2023

Energy-based Predictive Representations for Partially Observed Reinforcement Learning.

Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

Proceedings of the Uncertainty in Artificial Intelligence, 2023

AdaPlanner: Adaptive Planning from Feedback with Language Models.

Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Ordering-based Conditions for Global Convergence of Policy Gradient Methods.

Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Universal Policies via Text-Guided Video Generation.

Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Stochastic Gradient Succeeds for Bandits.

Jincheng Mei, Zixin Zhong, Bo Dai, Alekh Agarwal, Csaba Szepesvári, Dale Schuurmans

Proceedings of the International Conference on Machine Learning, 2023

Score-based Continuous-time Discrete Diffusion Models.

Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Any-scale Balanced Samplers for Discrete Space.

Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Spectral Decomposition Representation for Reinforcement Learning.

Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Latent Variable Representation for Reinforcement Learning.

Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval.

Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding.

Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Discrete Langevin Samplers via Wasserstein Gradient Flow.

Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Learning to Optimize with Stochastic Dominance Constraints.

Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Learning to Optimize with Stochastic Dominance Constraints.

Hanjun Dai, Yuan Xue, Niao He, Bethany Wang, Na Li, Dale Schuurmans, Bo Dai

CoRR, 2022

Discrete Langevin Sampler via Wasserstein Gradient Flow.

Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans

CoRR, 2022

SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition.

Dylan Slack, Yinlam Chow, Bo Dai, Nevan Wichers

CoRR, 2022

On the Effect of Log-Barrier Regularization in Decentralized Softmax Gradient Play in Multiagent Systems.

Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li

CoRR, 2022

Can Small Heads Help? Understanding and Improving Multi-Task Generalization.

Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Li Wei, Ed H. Chi

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

A free lunch from the noise: Provable and practical exploration for representation learning.

Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai

Proceedings of the Uncertainty in Artificial Intelligence, 2022

On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games.

Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Role of Baselines in Policy Gradient Optimization.

Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Oracle Inequalities for Model Selection in Offline Reinforcement Learning.

Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs.

Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Making Linear MDPs Practical via Contrastive Representation Learning.

Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai

Proceedings of the International Conference on Machine Learning, 2022

Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization.

Hanjun Dai, Mengjiao Yang, Yuan Xue, Dale Schuurmans, Bo Dai

Proceedings of the International Conference on Machine Learning, 2022

Model Selection in Batch Policy Optimization.

Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai

Proceedings of the International Conference on Machine Learning, 2022

Understanding and Leveraging Overparameterization in Recursive Value Estimation.

Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans

Proceedings of the Tenth International Conference on Learning Representations, 2022

Neural Stochastic Dual Dynamic Programming.

Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai

Proceedings of the Tenth International Conference on Learning Representations, 2022

SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction.

Qifan Wang, Li Yang, Jingang Wang, Jitin Krishnan, Bo Dai, Sinong Wang, Zenglin Xu, Madian Khabsa, Hao Ma

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Offline Policy Selection under Uncertainty.

Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

The Curse of Passive Data Collection in Batch Reinforcement Learning.

Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Self-Adaptive Imitation Learning: Learning Tasks with Delayed Rewards from Sub-optimal Demonstrations.

Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data.

Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári

CoRR, 2021

Towards understanding retrosynthesis by energy-based models.

Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Nearly Horizon-Free Offline Reinforcement Learning.

Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Combiner: Full Attention Transformer with Sparse Computation Cost.

Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding the Effect of Stochasticity in Policy Optimization.

Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Optimality of Batch Policy Optimization Algorithms.

Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans

Proceedings of the 38th International Conference on Machine Learning, 2021

LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs.

Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou

Proceedings of the 38th International Conference on Machine Learning, 2021

Leveraging Non-uniformity in First-order Non-convex Optimization.

Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvári, Dale Schuurmans

Proceedings of the 38th International Conference on Machine Learning, 2021

Overcoming Catastrophic Forgetting by Bayesian Generative Regularization.

Pei-Hung Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai

Proceedings of the 38th International Conference on Machine Learning, 2021

Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach.

Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning to Defend by Learning to Attack.

Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Small Towers Make Big Differences.

Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Ed H. Chi

CoRR, 2020

Energy-based View of Retrosynthesis.

Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai

CoRR, 2020

Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach.

Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Zhaoran Wang, Mladen Kolar

CoRR, 2020

Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations.

Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou

CoRR, 2020

Differentiable Top-k Operator with Optimal Transport.

Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

CoRR, 2020

Reinforcement Learning via Fenchel-Rockafellar Duality.

Ofir Nachum, Bo Dai

CoRR, 2020

Off-Policy Imitation Learning from Observations.

Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Off-Policy Evaluation via the Regularized Lagrangian.

Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Top-k with Optimal Transport.

Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Escaping the Gravitational Pull of Softmax.

Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach.

Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration.

Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

CoinDICE: Off-Policy Confidence Interval Estimation.

Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Energy-Based Processes for Exchangeable Data.

Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans

Proceedings of the 37th International Conference on Machine Learning, 2020

Batch Stationary Distribution Estimation.

Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans

Proceedings of the 37th International Conference on Machine Learning, 2020

Scalable Deep Generative Modeling for Sparse Graphs.

Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans

Proceedings of the 37th International Conference on Machine Learning, 2020

GenDICE: Generalized Offline Estimation of Stationary Values.

Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees.

Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

AlgaeDICE: Policy Gradient from Arbitrary Experience.

Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans

CoRR, 2019

Overcoming Catastrophic Forgetting by Generative Regularization.

Patrick H. Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai

CoRR, 2019

Learning to Plan via Neural Exploration-Exploitation Trees.

Binghong Chen, Bo Dai, Le Song

CoRR, 2019

Meta Architecture Search.

Albert E. Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections.

Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Energy-Inspired Models: Learning with Sampler-Induced Distributions.

Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Exponential Family Estimation via Adversarial Dynamics Embedding.

Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Retrosynthesis Prediction with Conditional Graph Logic Network.

Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Revisiting Auxiliary Latent Variables in Generative Models.

Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Learning to Defense by Learning to Attack.

Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Kernel Exponential Family Estimation via Doubly Dual Embedding.

Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning over functions, distributions and dynamics via stochastic optimization.

Bo Dai

PhD thesis, 2018

Bayesian Meta-network Architecture Learning.

Albert E. Shaw, Bo Dai, Weiyang Liu, Le Song

CoRR, 2018

Learning to Defense by Learning to Attack.

Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao

CoRR, 2018

Learning Deep Hidden Nonlinear Dynamics from Aggregate Data.

Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Predictive Approximate Bayesian Computation via Saddle Points.

Yingxiang Yang, Bo Dai, Negar Kiyavash, Niao He

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification.

Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning towards Minimum Hyperspherical Energy.

Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Coupled Variational Bayes via Optimization Embedding.

Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Structured Inference for Recurrent Hidden Semi-markov Model.

Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Towards Black-box Iterative Machine Teaching.

Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg, Le Song

Proceedings of the 35th International Conference on Machine Learning, 2018

SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation.

Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Steady-States of Iterative Algorithms over Graphs.

Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song

Proceedings of the 35th International Conference on Machine Learning, 2018

Syntax-Directed Variational Autoencoder for Structured Data.

Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song

Proceedings of the 6th International Conference on Learning Representations, 2018

Boosting the Actor with Dual Critic.

Bo Dai, Albert E. Shaw, Niao He, Lihong Li, Le Song

Proceedings of the 6th International Conference on Learning Representations, 2018

Decoupled Networks.

Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Multi-scale Nystrom Method.

Woosang Lim, Rundong Du, Bo Dai, Kyomin Jung, Le Song, Haesun Park

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Smoothed Dual Embedding Control.

Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Jianshu Chen, Le Song

CoRR, 2017

Deep Hyperspherical Learning.

Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song

CoRR, 2017

Towards Black-box Iterative Machine Teaching.

Weiyang Liu, Bo Dai, Xingguo Li, James M. Rehg, Le Song

CoRR, 2017

Iterative Machine Teaching.

Weiyang Liu, Bo Dai, James M. Rehg, Le Song

CoRR, 2017

Deep Hyperspherical Learning.

Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning from semantically dependent multi-tasks.

Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, Shandian Zhe

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Iterative Machine Teaching.

Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg, Le Song

Proceedings of the 34th International Conference on Machine Learning, 2017

Stochastic Generative Hashing.

Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song

Proceedings of the 34th International Conference on Machine Learning, 2017

Recurrent Hidden Semi-Markov Model.

Hanjun Dai, Bo Dai, Yan-Ming Zhang, Shuang Li, Le Song

Proceedings of the 5th International Conference on Learning Representations, 2017

Learning from Conditional Distributions via Dual Embeddings.

Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

A Context-Aware Framework for Reducing Bandwidth Usage of Mobile Video Chats.

Xin Qi, Qing Yang, David T. Nguyen, Ge Peng, Gang Zhou, Bo Dai, Daqing Zhang, Yantao Li

IEEE Trans. Multim., 2016

Learning from Conditional Distributions via Dual Kernel Embeddings.

Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song

CoRR, 2016

Discriminative Embeddings of Latent Variable Models for Structured Data.

Hanjun Dai, Bo Dai, Le Song

Proceedings of the 33nd International Conference on Machine Learning, 2016

Provable Bayesian Inference via Particle Mirror Descent.

Bo Dai, Niao He, Hanjun Dai, Le Song

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Scalable Bayesian Inference via Particle Mirror Descent.

Bo Dai, Niao He, Hanjun Dai, Le Song

CoRR, 2015

2014

Information-Theoretic Semi-Supervised Metric Learning via Entropy Regularization.

Gang Niu, Bo Dai, Makoto Yamada, Masashi Sugiyama

Neural Comput., 2014

Scalable Kernel Methods via Doubly Stochastic Gradients.

Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Nonparametric Estimation of Multi-View Latent Variable Models.

Le Song, Animashree Anandkumar, Bo Dai, Bo Xie

Proceedings of the 31th International Conference on Machine Learning, 2014

Transductive Learning with Multi-class Volume Approximation.

Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Maximum volume clustering: a new discriminative clustering approach.

Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama

J. Mach. Learn. Res., 2013

Robust Low Rank Kernel Embeddings of Multivariate Distributions.

Le Song, Bo Dai

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning.

Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama

Proceedings of the 30th International Conference on Machine Learning, 2013

2011

Maximum Volume Clustering.

Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2010

Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering.

Bo Dai, Bao-Gang Hu

Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Rough Margin Based Core Vector Machine.

Gang Niu, Bo Dai, Lin Shang, Yangsheng Ji

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

Compact Margin Machine.

Bo Dai, Gang Niu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

A Multiple Instance Approach for Keyword-Based Retrieval in Un-annotated Image Database.

Jun Jiao, Chen Shen, Bo Dai, Xuan Mo

Proceedings of the Advances in Multimedia Modeling, 2010

Neural-network based regression model with prior from ranking information.

Yajun Qu, Bo Dai, Bao-Gang Hu

Proceedings of the International Joint Conference on Neural Networks, 2010

Bayesian Maximum Margin Clustering.

Bo Dai, Bao-Gang Hu, Gang Niu

Proceedings of the ICDM 2010, 2010