Bayesian Maximum Margin Clustering. - Bo Dai 001; Bao-Gang Hu; Gang Niu 001 (ICDM, 2010)

Neural-network based regression model with prior from ranking information. - Yajun Qu; Bo Dai 001; Bao-Gang Hu (IJCNN, 2010)

A Multiple Instance Approach for Keyword-Based Retrieval in Un-annotated Image Database. - Jun Jiao; Chen Shen; Bo Dai 001; Xuan Mo (MMM, 2010)

Compact Margin Machine. - Bo Dai 001; Gang Niu 001 (PAKDD (2), 2010)

Rough Margin Based Core Vector Machine. - Gang Niu 001; Bo Dai 001; Lin Shang 001; Yangsheng Ji (PAKDD (1), 2010)

Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering. - Bo Dai 001; Bao-Gang Hu (ACML, 2010)

Maximum Volume Clustering. - Gang Niu 001; Bo Dai 001; Lin Shang 001; Masashi Sugiyama (AISTATS, 2011)

Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning. - Gang Niu 001; Wittawat Jitkrittum; Bo Dai 001; Hirotaka Hachiya; Masashi Sugiyama (ICML (3), 2013)

Robust Low Rank Kernel Embeddings of Multivariate Distributions. - Le Song; Bo Dai 001 (NIPS, 2013)

Maximum volume clustering: a new discriminative clustering approach. - Gang Niu 001; Bo Dai 001; Lin Shang 001; Masashi Sugiyama (J. Mach. Learn. Res., 2013)

Transductive Learning with Multi-class Volume Approximation. - Gang Niu 001; Bo Dai 001; Marthinus Christoffel du Plessis; Masashi Sugiyama (ICML, 2014)

Nonparametric Estimation of Multi-View Latent Variable Models. - Le Song; Animashree Anandkumar; Bo Dai 001; Bo Xie 002 (ICML, 2014)

Scalable Kernel Methods via Doubly Stochastic Gradients. - Bo Dai 001; Bo Xie 002; Niao He; Yingyu Liang; Anant Raj; Maria-Florina Balcan; Le Song (NIPS, 2014)

Information-Theoretic Semi-Supervised Metric Learning via Entropy Regularization. - Gang Niu 001; Bo Dai 001; Makoto Yamada; Masashi Sugiyama (Neural Comput., 2014)

Scalable Bayesian Inference via Particle Mirror Descent. - Bo Dai 001; Niao He; Hanjun Dai; Le Song (CoRR, 2015)

Provable Bayesian Inference via Particle Mirror Descent. - Bo Dai 001; Niao He; Hanjun Dai; Le Song (AISTATS, 2016)

Discriminative Embeddings of Latent Variable Models for Structured Data. - Hanjun Dai; Bo Dai 001; Le Song (ICML, 2016)

Learning from Conditional Distributions via Dual Kernel Embeddings. - Bo Dai 001; Niao He; Yunpeng Pan; Byron Boots; Le Song (CoRR, 2016)

A Context-Aware Framework for Reducing Bandwidth Usage of Mobile Video Chats. - Xin Qi 001; Qing Yang 005; David T. Nguyen; Ge Peng; Gang Zhou; Bo Dai 001; Daqing Zhang 001; Yantao Li 001 (IEEE Trans. Multim., 2016)

Learning from Conditional Distributions via Dual Embeddings. - Bo Dai 001; Niao He; Yunpeng Pan; Byron Boots; Le Song (AISTATS, 2017)

Recurrent Hidden Semi-Markov Model. - Hanjun Dai; Bo Dai 001; Yan-Ming Zhang; Shuang Li 002; Le Song (ICLR (Poster), 2017)

Stochastic Generative Hashing. - Bo Dai 001; Ruiqi Guo; Sanjiv Kumar; Niao He; Le Song (ICML, 2017)

Iterative Machine Teaching. - Weiyang Liu; Bo Dai 001; Ahmad Humayun; Charlene Tay; Chen Yu 001; Linda B. Smith; James M. Rehg; Le Song (ICML, 2017)

Learning from semantically dependent multi-tasks. - Bin Liu 022; Zenglin Xu; Bo Dai 001; Haoli Bai; Xianghong Fang; Yazhou Ren 001; Shandian Zhe (IJCNN, 2017)

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

Iterative Machine Teaching. - Weiyang Liu; Bo Dai 001; James M. Rehg; Le Song (CoRR, 2017)

Towards Black-box Iterative Machine Teaching. - Weiyang Liu; Bo Dai 001; Xingguo Li; James M. Rehg; Le Song (CoRR, 2017)

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

Smoothed Dual Embedding Control. - Bo Dai 001; Albert E. Shaw; Lihong Li 001; Lin Xiao; Niao He; Jianshu Chen; Le Song (CoRR, 2017)

Multi-scale Nystrom Method. - Woosang Lim; Rundong Du; Bo Dai 001; Kyomin Jung; Le Song; Haesun Park (AISTATS, 2018)

Decoupled Networks. - Weiyang Liu; Zhen Liu 019; Zhiding Yu; Bo Dai 001; Rongmei Lin; Yisen Wang 001; James M. Rehg; Le Song (CVPR, 2018)

Boosting the Actor with Dual Critic. - Bo Dai 001; Albert E. Shaw; Niao He; Lihong Li 001; Le Song (ICLR (Poster), 2018)

Syntax-Directed Variational Autoencoder for Structured Data. - Hanjun Dai; Yingtao Tian; Bo Dai 001; Steven Skiena; Le Song (ICLR (Poster), 2018)

Learning Steady-States of Iterative Algorithms over Graphs. - Hanjun Dai; Zornitsa Kozareva; Bo Dai 001; Alexander J. Smola; Le Song (ICML, 2018)

SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation. - Bo Dai 001; Albert E. Shaw; Lihong Li 001; Lin Xiao; Niao He; Zhen Liu 019; Jianshu Chen; Le Song (ICML, 2018)

Towards Black-box Iterative Machine Teaching. - Weiyang Liu; Bo Dai 001; Xingguo Li; Zhen Liu 019; James M. Rehg; Le Song (ICML, 2018)

Structured Inference for Recurrent Hidden Semi-markov Model. - Hao Liu; Lirong He; Haoli Bai; Bo Dai 001; Kun Bai; Zenglin Xu (IJCAI, 2018)

Coupled Variational Bayes via Optimization Embedding. - Bo Dai 001; Hanjun Dai; Niao He; Weiyang Liu; Zhen Liu 019; Jianshu Chen; Lin Xiao; Le Song (NeurIPS, 2018)

Learning towards Minimum Hyperspherical Energy. - Weiyang Liu; Rongmei Lin; Zhen Liu 019; Lixin Liu; Zhiding Yu; Bo Dai 001; Le Song (NeurIPS, 2018)

Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. - Harsh Shrivastava 001; Eugene Bart; Bob Price; Hanjun Dai; Bo Dai 001; Srinivas Aluru (NeurIPS, 2018)

Predictive Approximate Bayesian Computation via Saddle Points. - Yingxiang Yang; Bo Dai 001; Negar Kiyavash; Niao He (NeurIPS, 2018)

Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. - Yisen Wang 001; Bo Dai 001; Lingkai Kong; Sarah Monazam Erfani; James Bailey 001; Hongyuan Zha (UAI, 2018)

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

Bayesian Meta-network Architecture Learning. - Albert E. Shaw; Bo Dai 001; Weiyang Liu; Le Song (CoRR, 2018)

Learning over functions, distributions and dynamics via stochastic optimization. - Bo Dai 001 (2018)

Kernel Exponential Family Estimation via Doubly Dual Embedding. - Bo Dai 001; Hanjun Dai; Arthur Gretton; Le Song; Dale Schuurmans; Niao He (AISTATS, 2019)

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

Revisiting Auxiliary Latent Variables in Generative Models. - Dieterich Lawson; George Tucker; Bo Dai 001; Rajesh Ranganath (DGS@ICLR, 2019)

Retrosynthesis Prediction with Conditional Graph Logic Network. - Hanjun Dai; Chengtao Li; Connor W. Coley; Bo Dai 001; Le Song (NeurIPS, 2019)

Exponential Family Estimation via Adversarial Dynamics Embedding. - Bo Dai 001; Zhen Liu 019; Hanjun Dai; Niao He; Arthur Gretton; Le Song; Dale Schuurmans (NeurIPS, 2019)

Energy-Inspired Models: Learning with Sampler-Induced Distributions. - Dieterich Lawson; George Tucker; Bo Dai 001; Rajesh Ranganath (NeurIPS, 2019)

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. - Ofir Nachum; Yinlam Chow; Bo Dai 001; Lihong Li 001 (NeurIPS, 2019)

Meta Architecture Search. - Albert E. Shaw; Wei Wei 019; Weiyang Liu; Le Song; Bo Dai 001 (NeurIPS, 2019)

Learning to Plan via Neural Exploration-Exploitation Trees. - Binghong Chen; Bo Dai 001; Le Song (CoRR, 2019)

Overcoming Catastrophic Forgetting by Generative Regularization. - Patrick H. Chen; Wei Wei 019; Cho-Jui Hsieh; Bo Dai 001 (CoRR, 2019)

AlgaeDICE: Policy Gradient from Arbitrary Experience. - Ofir Nachum; Bo Dai 001; Ilya Kostrikov; Yinlam Chow; Lihong Li 001; Dale Schuurmans (CoRR, 2019)

Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees. - Binghong Chen; Bo Dai 001; Qinjie Lin; Guo Ye; Han Liu 001; Le Song (ICLR, 2020)

GenDICE: Generalized Offline Estimation of Stationary Values. - Ruiyi Zhang; Bo Dai 001; Lihong Li 001; Dale Schuurmans (ICLR, 2020)

Scalable Deep Generative Modeling for Sparse Graphs. - Hanjun Dai; Azade Nazi; Yujia Li; Bo Dai 001; Dale Schuurmans (ICML, 2020)

Batch Stationary Distribution Estimation. - Junfeng Wen; Bo Dai 001; Lihong Li 001; Dale Schuurmans (ICML, 2020)

Energy-Based Processes for Exchangeable Data. - Mengjiao Yang 001; Bo Dai 001; Hanjun Dai; Dale Schuurmans (ICML, 2020)

CoinDICE: Off-Policy Confidence Interval Estimation. - Bo Dai 001; Ofir Nachum; Yinlam Chow; Lihong Li 001; Csaba Szepesvári; Dale Schuurmans (NeurIPS, 2020)

Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. - Hanjun Dai; Rishabh Singh; Bo Dai 001; Charles Sutton; Dale Schuurmans (NeurIPS, 2020)

Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach. - Luofeng Liao; You-Lin Chen; Zhuoran Yang; Bo Dai 001; Mladen Kolar; Zhaoran Wang 001 (NeurIPS, 2020)

Escaping the Gravitational Pull of Softmax. - Jincheng Mei; Chenjun Xiao; Bo Dai 001; Lihong Li 001; Csaba Szepesvári; Dale Schuurmans (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)

Off-Policy Evaluation via the Regularized Lagrangian. - Mengjiao Yang 001; Ofir Nachum; Bo Dai 001; Lihong Li 001; Dale Schuurmans (NeurIPS, 2020)

Off-Policy Imitation Learning from Observations. - Zhuangdi Zhu; Kaixiang Lin; Bo Dai 001; Jiayu Zhou (NeurIPS, 2020)

Reinforcement Learning via Fenchel-Rockafellar Duality. - Ofir Nachum; Bo Dai 001 (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)

Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations. - Zhuangdi Zhu; Kaixiang Lin; Bo Dai 001; Jiayu Zhou (CoRR, 2020)

Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach. - Luofeng Liao; You-Lin Chen; Zhuoran Yang; Bo Dai 001; Zhaoran Wang 001; Mladen Kolar (CoRR, 2020)

Energy-based View of Retrosynthesis. - Ruoxi Sun 002; Hanjun Dai; Li Li 060; Steven Kearnes; Bo Dai 001 (CoRR, 2020)

Small Towers Make Big Differences. - Yuyan Wang; Zhe Zhao 001; Bo Dai 001; Christopher Fifty; Dong Lin; Lichan Hong; Ed H. Chi (CoRR, 2020)

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

Overcoming Catastrophic Forgetting by Bayesian Generative Regularization. - Pei-Hung Chen; Wei Wei 019; Cho-Jui Hsieh; Bo Dai 001 (ICML, 2021)

Leveraging Non-uniformity in First-order Non-convex Optimization. - Jincheng Mei; Yue Gao; Bo Dai 001; Csaba Szepesvári; Dale Schuurmans (ICML, 2021)

LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs. - Hongyu Ren; Hanjun Dai; Bo Dai 001; Xinyun Chen; Michihiro Yasunaga; Haitian Sun; Dale Schuurmans; Jure Leskovec; Denny Zhou (ICML, 2021)

On the Optimality of Batch Policy Optimization Algorithms. - Chenjun Xiao; Yifan Wu; Jincheng Mei; Bo Dai 001; Tor Lattimore; Lihong Li 001; Csaba Szepesvári; Dale Schuurmans (ICML, 2021)

Understanding the Effect of Stochasticity in Policy Optimization. - Jincheng Mei; Bo Dai 001; Chenjun Xiao; Csaba Szepesvári; Dale Schuurmans (NeurIPS, 2021)

Combiner: Full Attention Transformer with Sparse Computation Cost. - Hongyu Ren; Hanjun Dai; Zihang Dai; Mengjiao Yang 001; Jure Leskovec; Dale Schuurmans; Bo Dai 001 (NeurIPS, 2021)

Nearly Horizon-Free Offline Reinforcement Learning. - Tongzheng Ren; Jialian Li; Bo Dai 001; Simon S. Du; Sujay Sanghavi (NeurIPS, 2021)

Towards understanding retrosynthesis by energy-based models. - Ruoxi Sun 002; Hanjun Dai; Li Li 060; Steven Kearnes; Bo Dai 001 (NeurIPS, 2021)

On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data. - Chenjun Xiao; Ilbin Lee; Bo Dai 001; Dale Schuurmans; Csaba Szepesvári (CoRR, 2021)

Self-Adaptive Imitation Learning: Learning Tasks with Delayed Rewards from Sub-optimal Demonstrations. - Zhuangdi Zhu; Kaixiang Lin; Bo Dai 001; Jiayu Zhou (AAAI, 2022)

The Curse of Passive Data Collection in Batch Reinforcement Learning. - Chenjun Xiao; Ilbin Lee; Bo Dai 001; Dale Schuurmans; Csaba Szepesvári (AISTATS, 2022)

Offline Policy Selection under Uncertainty. - Mengjiao Yang 001; Bo Dai 001; Ofir Nachum; George Tucker; Dale Schuurmans (AISTATS, 2022)

SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction. - Qifan Wang 001; Li Yang; Jingang Wang; Jitin Krishnan; Bo Dai 001; Sinong Wang; Zenglin Xu; Madian Khabsa; Hao Ma 001 (EMNLP (Findings), 2022)

Neural Stochastic Dual Dynamic Programming. - Hanjun Dai; Yuan Xue; Zia Syed; Dale Schuurmans; Bo Dai 001 (ICLR, 2022)

Understanding and Leveraging Overparameterization in Recursive Value Estimation. - Chenjun Xiao; Bo Dai 001; Jincheng Mei; Oscar A. Ramirez; Ramki Gummadi; Chris Harris 001; Dale Schuurmans (ICLR, 2022)

Model Selection in Batch Policy Optimization. - Jonathan Lee 002; George Tucker; Ofir Nachum; Bo Dai 001 (ICML, 2022)

Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization. - Hanjun Dai; Mengjiao Yang 001; Yuan Xue; Dale Schuurmans; Bo Dai 001 (ICML, 2022)

Making Linear MDPs Practical via Contrastive Representation Learning. - Tianjun Zhang; Tongzheng Ren; Mengjiao Yang 001; Joseph Gonzalez 001; Dale Schuurmans; Bo Dai 001 (ICML, 2022)

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. - Hongyu Ren; Hanjun Dai; Bo Dai 001; Xinyun Chen; Denny Zhou; Jure Leskovec; Dale Schuurmans (KDD, 2022)

Oracle Inequalities for Model Selection in Offline Reinforcement Learning. - Jonathan N. Lee; George Tucker; Ofir Nachum; Bo Dai 001; Emma Brunskill (NeurIPS, 2022)

The Role of Baselines in Policy Gradient Optimization. - Jincheng Mei; Wesley Chung; Valentin Thomas; Bo Dai 001; Csaba Szepesvári; Dale Schuurmans (NeurIPS, 2022)

On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games. - Runyu Zhang 001; Jincheng Mei; Bo Dai 001; Dale Schuurmans; Na Li 002 (NeurIPS, 2022)

A free lunch from the noise: Provable and practical exploration for representation learning. - Tongzheng Ren; Tianjun Zhang; Csaba Szepesvári; Bo Dai 001 (UAI, 2022)

Can Small Heads Help? Understanding and Improving Multi-Task Generalization. - Yuyan Wang; Zhe Zhao 001; Bo Dai 001; Christopher Fifty; Dong Lin; Lichan Hong; Li Wei; Ed H. Chi (WWW, 2022)

On the Effect of Log-Barrier Regularization in Decentralized Softmax Gradient Play in Multiagent Systems. - Runyu Zhang 001; Jincheng Mei; Bo Dai 001; Dale Schuurmans; Na Li 002 (CoRR, 2022)

SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition. - Dylan Slack; Yinlam Chow; Bo Dai 001; Nevan Wichers (CoRR, 2022)

Discrete Langevin Sampler via Wasserstein Gradient Flow. - Haoran Sun; Hanjun Dai; Bo Dai 001; Haomin Zhou 001; Dale Schuurmans (CoRR, 2022)

Learning to Optimize with Stochastic Dominance Constraints. - Hanjun Dai; Yuan Xue; Niao He; Bethany Wang; Na Li 002; Dale Schuurmans; Bo Dai 001 (CoRR, 2022)

Learning to Optimize with Stochastic Dominance Constraints. - Hanjun Dai; Yuan Xue; Niao He; Yixin Wang; Na Li 002; Dale Schuurmans; Bo Dai 001 (AISTATS, 2023)

Discrete Langevin Samplers via Wasserstein Gradient Flow. - Haoran Sun; Hanjun Dai; Bo Dai 001; Haomin Zhou 001; Dale Schuurmans (AISTATS, 2023)

Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. - Tongzheng Ren; Zhaolin Ren; Na Li 002; Bo Dai 001 (CDC, 2023)

On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. - Jiayi Chen; Hanjun Dai; Bo Dai 001; Aidong Zhang; Wei Wei 019 (EMNLP (Findings), 2023)

Latent Variable Representation for Reinforcement Learning. - Tongzheng Ren; Chenjun Xiao; Tianjun Zhang; Na Li 002; Zhaoran Wang 001; Sujay Sanghavi; Dale Schuurmans; Bo Dai 001 (ICLR, 2023)

Spectral Decomposition Representation for Reinforcement Learning. - Tongzheng Ren; Tianjun Zhang; Lisa Lee; Joseph E. Gonzalez; Dale Schuurmans; Bo Dai 001 (ICLR, 2023)

Any-scale Balanced Samplers for Discrete Space. - Haoran Sun; Bo Dai 001; Charles Sutton; Dale Schuurmans; Hanjun Dai (ICLR, 2023)

Score-based Continuous-time Discrete Diffusion Models. - Haoran Sun; Lijun Yu; Bo Dai 001; Dale Schuurmans; Hanjun Dai (ICLR, 2023)

Stochastic Gradient Succeeds for Bandits. - Jincheng Mei; Zixin Zhong; Bo Dai 001; Alekh Agarwal; Csaba Szepesvári; Dale Schuurmans (ICML, 2023)

Learning Universal Policies via Text-Guided Video Generation. - Yilun Du; Sherry Yang 001; Bo Dai 001; Hanjun Dai; Ofir Nachum; Josh Tenenbaum 001; Dale Schuurmans; Pieter Abbeel (NeurIPS, 2023)

Ordering-based Conditions for Global Convergence of Policy Gradient Methods. - Jincheng Mei; Bo Dai 001; Alekh Agarwal; Mohammad Ghavamzadeh; Csaba Szepesvári; Dale Schuurmans (NeurIPS, 2023)

AdaPlanner: Adaptive Planning from Feedback with Language Models. - Haotian Sun; Yuchen Zhuang; Lingkai Kong; Bo Dai 001; Chao Zhang 014 (NeurIPS, 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 001 (UAI, 2023)

Probabilistic Adaptation of Text-to-Video Models. - Mengjiao Yang 001; Yilun Du; Bo Dai 001; Dale Schuurmans; Joshua B. Tenenbaum; Pieter Abbeel (CoRR, 2023)

DF2: Distribution-Free Decision-Focused Learning. - Lingkai Kong; Wenhao Mu; Jiaming Cui; Yuchen Zhuang; B. Aditya Prakash; Bo Dai 001; Chao Zhang 014 (CoRR, 2023)

Probabilistic Adaptation of Black-Box Text-to-Video Models. - Sherry Yang 001; Yilun Du; Bo Dai 001; Dale Schuurmans; Joshua B. Tenenbaum; Pieter Abbeel (ICLR, 2024)

Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. - Fengdi Che; Chenjun Xiao; Jincheng Mei; Bo Dai 001; Ramki Gummadi; Oscar A. Ramirez; Christopher K. Harris; A. Rupam Mahmood; Dale Schuurmans (ICML, 2024)

BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models. - Haotian Sun; Yuchen Zhuang; Wei Wei 019; Chao Zhang 014; Bo Dai 001 (ICML, 2024)

Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. - Hongming Zhang 012; Tongzheng Ren; Chenjun Xiao; Dale Schuurmans; Bo Dai 001 (ICML, 2024)

Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint. - Haitong Ma; Zhaolin Ren; Bo Dai 001; Na Li 002 (IROS, 2024)

UQE: A Query Engine for Unstructured Databases. - Hanjun Dai; Bethany Wang; Xingchen Wan; Bo Dai 001; Sherry Yang 001; Azade Nova; Pengcheng Yin; Phitchaya Mangpo Phothilimthana; Charles Sutton; Dale Schuurmans (NeurIPS, 2024)

Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. - Jincheng Mei; Bo Dai 001; Alekh Agarwal; Sharan Vaswani; Anant Raj; Csaba Szepesvári; Dale Schuurmans (NeurIPS, 2024)

Diffusion Spectral Representation for Reinforcement Learning. - Dmitry Shribak; Chen-Xiao Gao; Yitong Li; Chenjun Xiao; Bo Dai 001 (NeurIPS, 2024)

HYDRA: Model Factorization Framework for Black-Box LLM Personalization. - Yuchen Zhuang; Haotian Sun; Yue Yu 001; Rushi Qiang; Qifan Wang 001; Chao Zhang 014; Bo Dai 001 (NeurIPS, 2024)

Beyond Expectations: Learning with Stochastic Dominance Made Practical. - Shicong Cen; Jincheng Mei; Hanjun Dai; Dale Schuurmans; Yuejie Chi; Bo Dai 001 (CoRR, 2024)

VideoAgent: Self-Improving Video Generation. - Achint Soni; Sreyas Venkataraman; Abhranil Chandra; Sebastian Fischmeister; Percy Liang; Bo Dai 001; Sherry Yang 001 (CoRR, 2024)

Scalable spectral representations for network multiagent control. - Zhaolin Ren; Runyu Zhang 001; Bo Dai 001; Na Li 002 (CoRR, 2024)

Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment. - Tong Yang 007; Jincheng Mei; Hanjun Dai; Zixin Wen; Shicong Cen; Dale Schuurmans; Yuejie Chi; Bo Dai 001 (CoRR, 2024)

Matryoshka: Learning to Drive Black-Box LLMs with LLMs. - Changhao Li; Yuchen Zhuang; Rushi Qiang; Haotian Sun; Hanjun Dai; Chao Zhang 014; Bo Dai 001 (CoRR, 2024)

Primal-Dual Spectral Representation for Off-policy Evaluation. - Yang Hu; Tianyi Chen; Na Li 002; Kai Wang; Bo Dai 001 (AISTATS, 2025)

Scalable spectral representations for multiagent reinforcement learning in network MDPs. - Zhaolin Ren; Runyu Zhang 001; Bo Dai 001; Na Li 002 (AISTATS, 2025)

Spectral Representation for Causal Estimation with Hidden Confounders. - Haotian Sun; Antoine Moulin; Tongzheng Ren; Arthur Gretton; Bo Dai 001 (AISTATS, 2025)

Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment. - Tong Yang 007; Jincheng Mei; Hanjun Dai; Zixin Wen; Shicong Cen; Dale Schuurmans; Yuejie Chi; Bo Dai 001 (AISTATS, 2025)

Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. - Shicong Cen; Jincheng Mei; Katayoon Goshvadi; Hanjun Dai; Tong Yang 007; Sherry Yang 001; Dale Schuurmans; Yuejie Chi; Bo Dai 001 (ICLR, 2025)

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. - Yinlam Chow; Guy Tennenholtz; Izzeddin Gur; Vincent Zhuang; Bo Dai 001; Aviral Kumar; Rishabh Agarwal; Sridhar Thiagarajan; Craig Boutilier; Aleksandra Faust (ICLR, 2025)

EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing. - Haotian Sun; Tao Lei; Bowen Zhang; Yanghao Li; Haoshuo Huang; Ruoming Pang; Bo Dai 001; Nan Du (ICLR, 2025)

Efficient Duple Perturbation Robustness in Low-rank MDPs. - Yang Hu; Haitong Ma; Na Li 002; Bo Dai 001 (L4DC, 2025)

DF2: Distribution-Free Decision-Focused Learning. - Lingkai Kong; Wenhao Mu; Jiaming Cui; Yuchen Zhuang; B. Aditya Prakash; Bo Dai 001; Chao Zhang 014 (UAI, 2025)

Soft Diffusion Actor-Critic: Efficient Online Reinforcement Learning for Diffusion Policy. - Haitong Ma; Tianyi Chen; Kai Wang; Na Li 002; Bo Dai 001 (CoRR, 2025)

Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games. - Tong Yang 007; Bo Dai 001; Lin Xiao; Yuejie Chi (CoRR, 2025)

Representation Learning via Non-Contrastive Mutual Information. - Zhaohan Daniel Guo; Bernardo Ávila Pires; Khimya Khetarpal; Dale Schuurmans; Bo Dai 001 (CoRR, 2025)

Rethinking the Global Convergence of Softmax Policy Gradient with Linear Function Approximation. - Max Qiushi Lin; Jincheng Mei; Matin Aghaei; Michael Lu; Bo Dai 001; Alekh Agarwal; Dale Schuurmans; Csaba Szepesvári; Sharan Vaswani (CoRR, 2025)

MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering. - Rushi Qiang; Yuchen Zhuang; Yinghao Li; Dingu Sagar V. K; Rongzhi Zhang; Changhao Li; Ian Shu-Hei Wong; Sherry Yang 001; Percy Liang; Chao Zhang 014; Bo Dai 001 (CoRR, 2025)

AmorLIP: Efficient Language-Image Pretraining via Amortization. - Haotian Sun; Yitong Li; Yuchen Zhuang; Niao He; Hanjun Dai; Bo Dai 001 (CoRR, 2025)

Towards Better Instruction Following Retrieval Models. - Yuchen Zhuang; Aaron Trinh; Rushi Qiang; Haotian Sun; Chao Zhang 014; Hanjun Dai; Bo Dai 001 (CoRR, 2025)

Learning Task-Agnostic Skill Bases to Uncover Motor Primitives in Animal Behaviors. - Jiyi Wang; Jingyang Ke; Bo Dai 001; Anqi Wu (CoRR, 2025)

Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL. - Tong Yang 007; Bo Dai 001; Lin Xiao; Yuejie Chi (CoRR, 2025)

Spectral Bellman Method: Unifying Representation and Exploration in RL. - Ofir Nabati; Bo Dai 001; Shie Mannor; Guy Tennenholtz (CoRR, 2025)

One-Step Flow Policy Mirror Descent. - Tianyi Chen; Haitong Ma; Na Li 002; Kai Wang; Bo Dai 001 (CoRR, 2025)

Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations. - Haitong Ma; Bo Dai 001; Zhaolin Ren; Yebin Wang; Na Li 002 (CoRR, 2025)