Bo Dai - RankMe

233 papers A* 73A 20B 3C 1Journal 119Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective. CoRR Yinan Huang, Hans Hao-Hsun Hsu, Junran Wang, Bo Dai, Pan Li
2026	J	`jnl`	Beyond Expectations: Learning with Stochastic Dominance Made Practical. Trans. Mach. Learn. Res. Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai
2026	J	`jnl`	Diffusion Controller: Framework, Algorithms and Parameterization. CoRR Tong Yang, Moonkyung Ryu, Chih-Wei Hsu, Guy Tennenholtz, Yuejie Chi, Craig Boutilier, Bo Dai
2026	J	`jnl`	FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies. CoRR Chenxiao Gao, Edward Chen, Tianyi Chen, Bo Dai
2026	J	`jnl`	SiMPO: Measure Matching for Online Diffusion Reinforcement Learning. CoRR Haitong Ma, Chenxiao Gao, Tianyi Chen, Na Li, Bo Dai
2026	J	`jnl`	Spectral Ghost in Representation Learning: from Component Analysis to Self-Supervised Learning. CoRR Bo Dai, Na Li, Dale Schuurmans
2025	J	`jnl`	AmorLIP: Efficient Language-Image Pretraining via Amortization. CoRR Haotian Sun, Yitong Li, Yuchen Zhuang, Niao He, Hanjun Dai, Bo Dai
2025	J	`jnl`	An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation. CoRR Uzair Akbar, Niki Kilbertus, Hao Shen, Krikamol Muandet, Bo Dai
2025	A	`conf`	DF UAI Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang
2025	A*	`conf`	EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing. ICLR Haotian Sun, Tao Lei, Bowen Zhang, Yanghao Li, Haoshuo Huang, Ruoming Pang, Bo Dai, Nan Du
2025	—	`conf`	Efficient Duple Perturbation Robustness in Low-rank MDPs. L4DC Yang Hu, Haitong Ma, Na Li, Bo Dai
2025	A*	`conf`	Efficient Online Reinforcement Learning for Diffusion Policy. ICML Haitong Ma, Tianyi Chen, Kai Wang, Na Li, Bo Dai
2025	J	`jnl`	Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL. CoRR Tong Yang, Bo Dai, Lin Xiao, Yuejie Chi
2025	A	`conf`	Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment. AISTATS Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai
2025	A*	`conf`	Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games. ICML Tong Yang, Bo Dai, Lin Xiao, Yuejie Chi
2025	J	`jnl`	Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games. CoRR Tong Yang, Bo Dai, Lin Xiao, Yuejie Chi
2025	A*	`conf`	Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. ICLR Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust
2025	J	`jnl`	Judging with Confidence: Calibrating Autoraters to Preference Distributions. CoRR Zhuohang Li, Xiaowei Li, Chengyu Huang, Guowang Li, Katayoon Goshvadi, Bo Dai, Dale Schuurmans, Paul Zhou, Hamid Palangi, Yiwen Song, Palash Goyal, Murat Kantarcioglu, Bradley A. Malin, Yuan Xue
2025	J	`jnl`	Learning Task-Agnostic Skill Bases to Uncover Motor Primitives in Animal Behaviors. CoRR Jiyi Wang, Jingyang Ke, Bo Dai, Anqi Wu
2025	J	`jnl`	MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering. CoRR Rushi Qiang, Yuchen Zhuang, Yinghao Li, Dingu Sagar V. K, Rongzhi Zhang, Changhao Li, Ian Shu-Hei Wong, Sherry Yang, Percy Liang, Chao Zhang, Bo Dai
2025	J	`jnl`	MLE-Smith: Scaling MLE Tasks with Automated Multi-Agent Pipeline. CoRR Rushi Qiang, Yuchen Zhuang, Anikait Singh, Percy Liang, Chao Zhang, Sherry Yang, Bo Dai
2025	J	`jnl`	Max-Entropy Reinforcement Learning with Flow Matching and A Case Study on LQR. CoRR Yuyang Zhang, Yang Hu, Bo Dai, Na Li
2025	A	`conf`	Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations. IROS Haitong Ma, Bo Dai, Zhaolin Ren, Yebin Wang, Na Li
2025	J	`jnl`	Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations. CoRR Haitong Ma, Bo Dai, Zhaolin Ren, Yebin Wang, Na Li
2025	J	`jnl`	One-Step Flow Policy Mirror Descent. CoRR Tianyi Chen, Haitong Ma, Na Li, Kai Wang, Bo Dai
2025	J	`jnl`	Ordering-based Conditions for Global Convergence of Policy Gradient Methods. CoRR Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans
2025	A	`conf`	Primal-Dual Spectral Representation for Off-policy Evaluation. AISTATS Yang Hu, Tianyi Chen, Na Li, Kai Wang, Bo Dai
2025	J	`jnl`	Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces. CoRR Haitong Ma, Ofir Nabati, Aviv Rosenberg, Bo Dai, Oran Lang, Idan Szpektor, Craig Boutilier, Na Li, Shie Mannor, Lior Shani, Guy Tennenholtz
2025	J	`jnl`	Representation Learning via Non-Contrastive Mutual Information. CoRR Zhaohan Daniel Guo, Bernardo Ávila Pires, Khimya Khetarpal, Dale Schuurmans, Bo Dai
2025	J	`jnl`	Rethinking the Global Convergence of Softmax Policy Gradient with Linear Function Approximation. CoRR Max Qiushi Lin, Jincheng Mei, Matin Aghaei, Michael Lu, Bo Dai, Alekh Agarwal, Dale Schuurmans, Csaba Szepesvári, Sharan Vaswani
2025	A	`conf`	Scalable spectral representations for multiagent reinforcement learning in network MDPs. AISTATS Zhaolin Ren, Runyu Zhang, Bo Dai, Na Li
2025	J	`jnl`	Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. CoRR Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans
2025	J	`jnl`	Soft Diffusion Actor-Critic: Efficient Online Reinforcement Learning for Diffusion Policy. CoRR Haitong Ma, Tianyi Chen, Kai Wang, Na Li, Bo Dai
2025	J	`jnl`	Spectral Bellman Method: Unifying Representation and Exploration in RL. CoRR Ofir Nabati, Bo Dai, Shie Mannor, Guy Tennenholtz
2025	A	`conf`	Spectral Representation for Causal Estimation with Hidden Confounders. AISTATS Haotian Sun, Antoine Moulin, Tongzheng Ren, Arthur Gretton, Bo Dai
2025	J	`jnl`	Spectral Representation-based Reinforcement Learning. CoRR Chenxiao Gao, Haotian Sun, Na Li, Dale Schuurmans, Bo Dai
2025	J	`jnl`	Stochastic Nonlinear Control via Finite-Dimensional Spectral Dynamics Embedding. IEEE Trans. Autom. Control. Zhaolin Ren, Tongzheng Ren, Haitong Ma, Na Li, Bo Dai
2025	J	`jnl`	Towards Better Instruction Following Retrieval Models. CoRR Yuchen Zhuang, Aaron Trinh, Rushi Qiang, Haotian Sun, Chao Zhang, Hanjun Dai, Bo Dai
2025	A*	`conf`	Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. ICLR Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	A*	`conf`	BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models. ICML Haotian Sun, Yuchen Zhuang, Wei Wei, Chao Zhang, Bo Dai
2024	J	`jnl`	BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models. CoRR Haotian Sun, Yuchen Zhuang, Wei Wei, Chao Zhang, Bo Dai
2024	J	`jnl`	Beyond Expectations: Learning with Stochastic Dominance Made Practical. CoRR Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	A*	`conf`	Diffusion Spectral Representation for Reinforcement Learning. NeurIPS Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai
2024	J	`jnl`	Diffusion Spectral Representation for Reinforcement Learning. CoRR Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai
2024	J	`jnl`	EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing. CoRR Haotian Sun, Tao Lei, Bowen Zhang, Yanghao Li, Haoshuo Huang, Ruoming Pang, Bo Dai, Nan Du
2024	J	`jnl`	Efficient Duple Perturbation Robustness in Low-rank MDPs. CoRR Yang Hu, Haitong Ma, Bo Dai, Na Li
2024	J	`jnl`	Faster WIND: Accelerating Iterative Best-of- CoRR Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	A*	`conf`	HYDRA: Model Factorization Framework for Black-Box LLM Personalization. NeurIPS Yuchen Zhuang, Haotian Sun, Yue Yu, Rushi Qiang, Qifan Wang, Chao Zhang, Bo Dai
2024	J	`jnl`	HYDRA: Model Factorization Framework for Black-Box LLM Personalization. CoRR Yuchen Zhuang, Haotian Sun, Yue Yu, Rushi Qiang, Qifan Wang, Chao Zhang, Bo Dai
2024	J	`jnl`	Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. CoRR Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Sridhar Thiagarajan, Craig Boutilier, Rishabh Agarwal, Aviral Kumar, Aleksandra Faust
2024	J	`jnl`	Matryoshka: Learning to Drive Black-Box LLMs with LLMs. CoRR Changhao Li, Yuchen Zhuang, Rushi Qiang, Haotian Sun, Hanjun Dai, Chao Zhang, Bo Dai
2024	J	`jnl`	Primal-Dual Spectral Representation for Off-policy Evaluation. CoRR Yang Hu, Tianyi Chen, Na Li, Kai Wang, Bo Dai
2024	A*	`conf`	Probabilistic Adaptation of Black-Box Text-to-Video Models. ICLR Sherry Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B. Tenenbaum, Pieter Abbeel
2024	A*	`conf`	Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. ICML Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai
2024	J	`jnl`	Scalable spectral representations for network multiagent control. CoRR Zhaolin Ren, Runyu Zhang, Bo Dai, Na Li
2024	A	`conf`	Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint. IROS Haitong Ma, Zhaolin Ren, Bo Dai, Na Li
2024	J	`jnl`	Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint. CoRR Haitong Ma, Zhaolin Ren, Bo Dai, Na Li
2024	A*	`conf`	Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. NeurIPS Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans
2024	J	`jnl`	Spectral Representation for Causal Estimation with Hidden Confounders. CoRR Tongzheng Ren, Haotian Sun, Antoine Moulin, Arthur Gretton, Bo Dai
2024	J	`jnl`	Stochastic Gradient Succeeds for Bandits. CoRR Jincheng Mei, Zixin Zhong, Bo Dai, Alekh Agarwal, Csaba Szepesvári, Dale Schuurmans
2024	A*	`conf`	Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. ICML Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
2024	J	`jnl`	Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. CoRR Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
2024	A*	`conf`	UQE: A Query Engine for Unstructured Databases. NeurIPS Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
2024	J	`jnl`	UQE: A Query Engine for Unstructured Databases. CoRR Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
2024	J	`jnl`	Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. CoRR Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	J	`jnl`	VideoAgent: Self-Improving Video Generation. CoRR Achint Soni, Sreyas Venkataraman, Abhranil Chandra, Sebastian Fischmeister, Percy Liang, Bo Dai, Sherry Yang
2023	A*	`conf`	AdaPlanner: Adaptive Planning from Feedback with Language Models. NeurIPS Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang
2023	J	`jnl`	AdaPlanner: Adaptive Planning from Feedback with Language Models. CoRR Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang
2023	A*	`conf`	Any-scale Balanced Samplers for Discrete Space. ICLR Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai
2023	J	`jnl`	DF2: Distribution-Free Decision-Focused Learning. CoRR Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang
2023	A	`conf`	Discrete Langevin Samplers via Wasserstein Gradient Flow. AISTATS Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans
2023	A	`conf`	Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
2023	A*	`conf`	Latent Variable Representation for Reinforcement Learning. ICLR Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
2023	A*	`conf`	Learning Universal Policies via Text-Guided Video Generation. NeurIPS Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel
2023	J	`jnl`	Learning Universal Policies via Text-Guided Video Generation. CoRR Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel
2023	A	`conf`	Learning to Optimize with Stochastic Dominance Constraints. AISTATS Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai
2023	—	`conf`	On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. EMNLP (Findings) Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei
2023	J	`jnl`	On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. CoRR Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei
2023	A*	`conf`	Ordering-based Conditions for Global Convergence of Policy Gradient Methods. NeurIPS Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans
2023	J	`jnl`	Probabilistic Adaptation of Text-to-Video Models. CoRR Mengjiao Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B. Tenenbaum, Pieter Abbeel
2023	J	`jnl`	Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. CoRR Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai
2023	A*	`conf`	Score-based Continuous-time Discrete Diffusion Models. ICLR Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai
2023	A*	`conf`	Spectral Decomposition Representation for Reinforcement Learning. ICLR Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
2023	A*	`conf`	Stochastic Gradient Succeeds for Bandits. ICML Jincheng Mei, Zixin Zhong, Bo Dai, Alekh Agarwal, Csaba Szepesvári, Dale Schuurmans
2023	—	`conf`	Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. CDC Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai
2023	J	`jnl`	Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. CoRR Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai
2023	J	`jnl`	The Role of Baselines in Policy Gradient Optimization. CoRR Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvári, Dale Schuurmans
2022	A	`conf`	A free lunch from the noise: Provable and practical exploration for representation learning. UAI Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai
2022	A*	`conf`	Can Small Heads Help? Understanding and Improving Multi-Task Generalization. WWW Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Li Wei, Ed H. Chi
2022	J	`jnl`	Discrete Langevin Sampler via Wasserstein Gradient Flow. CoRR Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans
2022	J	`jnl`	Latent Variable Representation for Reinforcement Learning. CoRR Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
2022	J	`jnl`	Learning to Optimize with Stochastic Dominance Constraints. CoRR Hanjun Dai, Yuan Xue, Niao He, Bethany Wang, Na Li, Dale Schuurmans, Bo Dai
2022	A*	`conf`	Making Linear MDPs Practical via Contrastive Representation Learning. ICML Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai
2022	J	`jnl`	Making Linear MDPs Practical via Contrastive Representation Learning. CoRR Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
2022	A*	`conf`	Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization. ICML Hanjun Dai, Mengjiao Yang, Yuan Xue, Dale Schuurmans, Bo Dai
2022	A*	`conf`	Model Selection in Batch Policy Optimization. ICML Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai
2022	A*	`conf`	Neural Stochastic Dual Dynamic Programming. ICLR Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
2022	A	`conf`	Offline Policy Selection under Uncertainty. AISTATS Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans
2022	J	`jnl`	On the Effect of Log-Barrier Regularization in Decentralized Softmax Gradient Play in Multiagent Systems. CoRR Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li
2022	A*	`conf`	On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games. NeurIPS Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li
2022	A*	`conf`	Oracle Inequalities for Model Selection in Offline Reinforcement Learning. NeurIPS Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
2022	J	`jnl`	Oracle Inequalities for Model Selection in Offline Reinforcement Learning. CoRR Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
2022	J	`jnl`	SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition. CoRR Dylan Slack, Yinlam Chow, Bo Dai, Nevan Wichers
2022	—	`conf`	SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction. EMNLP (Findings) Qifan Wang, Li Yang, Jingang Wang, Jitin Krishnan, Bo Dai, Sinong Wang, Zenglin Xu, Madian Khabsa, Hao Ma
2022	A*	`conf`	SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. KDD Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
2022	J	`jnl`	Score-based Continuous-time Discrete Diffusion Models. CoRR Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai
2022	A*	`conf`	Self-Adaptive Imitation Learning: Learning Tasks with Delayed Rewards from Sub-optimal Demonstrations. AAAI Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou
2022	J	`jnl`	Spectral Decomposition Representation for Reinforcement Learning. CoRR Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
2022	A	`conf`	The Curse of Passive Data Collection in Batch Reinforcement Learning. AISTATS Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári
2022	A*	`conf`	The Role of Baselines in Policy Gradient Optimization. NeurIPS Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvári, Dale Schuurmans
2022	A*	`conf`	Understanding and Leveraging Overparameterization in Recursive Value Estimation. ICLR Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A. Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans
2021	J	`jnl`	A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning. CoRR Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai
2021	A*	`conf`	Combiner: Full Attention Transformer with Sparse Computation Cost. NeurIPS Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
2021	J	`jnl`	Combiner: Full Attention Transformer with Sparse Computation Cost. CoRR Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
2021	A*	`conf`	LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs. ICML Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou
2021	A	`conf`	Learning to Defend by Learning to Attack. AISTATS Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao
2021	A*	`conf`	Leveraging Non-uniformity in First-order Non-convex Optimization. ICML Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	Leveraging Non-uniformity in First-order Non-convex Optimization. CoRR Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	Model Selection in Batch Policy Optimization. CoRR Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai
2021	A*	`conf`	Nearly Horizon-Free Offline Reinforcement Learning. NeurIPS Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
2021	J	`jnl`	Nearly Horizon-Free Offline Reinforcement Learning. CoRR Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
2021	J	`jnl`	Neural Stochastic Dual Dynamic Programming. CoRR Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
2021	J	`jnl`	Off-Policy Imitation Learning from Observations. CoRR Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou
2021	A*	`conf`	On the Optimality of Batch Policy Optimization Algorithms. ICML Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	On the Optimality of Batch Policy Optimization Algorithms. CoRR Chenjun Xiao, Yifan Wu, Tor Lattimore, Bo Dai, Jincheng Mei, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data. CoRR Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári
2021	A*	`conf`	Overcoming Catastrophic Forgetting by Bayesian Generative Regularization. ICML Pei-Hung Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
2021	J	`jnl`	SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. CoRR Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
2021	—	`conf`	Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. EMNLP (1) Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei
2021	J	`jnl`	Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. CoRR Haoming Jiang, Bo Dai, Mengjiao Yang, Wei Wei, Tuo Zhao
2021	A*	`conf`	Towards understanding retrosynthesis by energy-based models. NeurIPS Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
2021	A*	`conf`	Understanding the Effect of Stochasticity in Policy Optimization. NeurIPS Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	Understanding the Effect of Stochasticity in Policy Optimization. CoRR Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2020	A*	`conf`	Batch Stationary Distribution Estimation. ICML Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans
2020	J	`jnl`	Batch Stationary Distribution Estimation. CoRR Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans
2020	A*	`conf`	CoinDICE: Off-Policy Confidence Interval Estimation. NeurIPS Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	CoinDICE: Off-Policy Confidence Interval Estimation. CoRR Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	Differentiable Top-k Operator with Optimal Transport. CoRR Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
2020	A*	`conf`	Differentiable Top-k with Optimal Transport. NeurIPS Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
2020	A*	`conf`	Energy-Based Processes for Exchangeable Data. ICML Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
2020	J	`jnl`	Energy-Based Processes for Exchangeable Data. CoRR Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
2020	J	`jnl`	Energy-based View of Retrosynthesis. CoRR Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
2020	A*	`conf`	Escaping the Gravitational Pull of Softmax. NeurIPS Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	A*	`conf`	GenDICE: Generalized Offline Estimation of Stationary Values. ICLR Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans
2020	J	`jnl`	GenDICE: Generalized Offline Estimation of Stationary Values. CoRR Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans
2020	A*	`conf`	Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. NeurIPS Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
2020	J	`jnl`	Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. CoRR Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
2020	J	`jnl`	Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations. CoRR Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou
2020	A*	`conf`	Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees. ICLR Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song
2020	A*	`conf`	Off-Policy Evaluation via the Regularized Lagrangian. NeurIPS Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans
2020	J	`jnl`	Off-Policy Evaluation via the Regularized Lagrangian. CoRR Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans
2020	A*	`conf`	Off-Policy Imitation Learning from Observations. NeurIPS Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou
2020	J	`jnl`	Offline Policy Selection under Uncertainty. CoRR Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans
2020	J	`jnl`	Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach. CoRR Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Zhaoran Wang, Mladen Kolar
2020	A*	`conf`	Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach. NeurIPS Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang
2020	J	`jnl`	Reinforcement Learning via Fenchel-Rockafellar Duality. CoRR Ofir Nachum, Bo Dai
2020	J	`jnl`	Retrosynthesis Prediction with Conditional Graph Logic Network. CoRR Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
2020	A*	`conf`	Scalable Deep Generative Modeling for Sparse Graphs. ICML Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
2020	J	`jnl`	Scalable Deep Generative Modeling for Sparse Graphs. CoRR Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
2020	J	`jnl`	Small Towers Make Big Differences. CoRR Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Ed H. Chi
2019	J	`jnl`	AlgaeDICE: Policy Gradient from Arbitrary Experience. CoRR Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans
2019	J	`jnl`	Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. CoRR Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
2019	A*	`conf`	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. NeurIPS Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
2019	J	`jnl`	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. CoRR Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
2019	A*	`conf`	Energy-Inspired Models: Learning with Sampler-Induced Distributions. NeurIPS Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath
2019	J	`jnl`	Energy-Inspired Models: Learning with Sampler-Induced Distributions. CoRR Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath
2019	A*	`conf`	Exponential Family Estimation via Adversarial Dynamics Embedding. NeurIPS Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans
2019	J	`jnl`	Exponential Family Estimation via Adversarial Dynamics Embedding. CoRR Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans
2019	A	`conf`	Kernel Exponential Family Estimation via Doubly Dual Embedding. AISTATS Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
2019	—	`conf`	Learning to Defense by Learning to Attack. DGS@ICLR Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao
2019	J	`jnl`	Learning to Plan via Neural Exploration-Exploitation Trees. CoRR Binghong Chen, Bo Dai, Le Song
2019	A*	`conf`	Meta Architecture Search. NeurIPS Albert E. Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai
2019	J	`jnl`	Overcoming Catastrophic Forgetting by Generative Regularization. CoRR Patrick H. Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
2019	A*	`conf`	Retrosynthesis Prediction with Conditional Graph Logic Network. NeurIPS Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
2019	—	`conf`	Revisiting Auxiliary Latent Variables in Generative Models. DGS@ICLR Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath
2018	J	`jnl`	Bayesian Meta-network Architecture Learning. CoRR Albert E. Shaw, Bo Dai, Weiyang Liu, Le Song
2018	—	`conf`	Boosting the Actor with Dual Critic. ICLR (Poster) Bo Dai, Albert E. Shaw, Niao He, Lihong Li, Le Song
2018	A*	`conf`	Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. NeurIPS Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
2018	A*	`conf`	Coupled Variational Bayes via Optimization Embedding. NeurIPS Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song
2018	A*	`conf`	Decoupled Networks. CVPR Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song
2018	J	`jnl`	Decoupled Networks. CoRR Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song
2018	J	`jnl`	Kernel Exponential Family Estimation via Doubly Dual Embedding. CoRR Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
2018	A	`conf`	Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. UAI Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha
2018	J	`jnl`	Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. CoRR Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha
2018	A*	`conf`	Learning Steady-States of Iterative Algorithms over Graphs. ICML Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song
2018	—	`—`	Learning over functions, distributions and dynamics via stochastic optimization. Bo Dai
2018	J	`jnl`	Learning to Defense by Learning to Attack. CoRR Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao
2018	A*	`conf`	Learning towards Minimum Hyperspherical Energy. NeurIPS Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song
2018	J	`jnl`	Learning towards Minimum Hyperspherical Energy. CoRR Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song
2018	A	`conf`	Multi-scale Nystrom Method. AISTATS Woosang Lim, Rundong Du, Bo Dai, Kyomin Jung, Le Song, Haesun Park
2018	A*	`conf`	Predictive Approximate Bayesian Computation via Saddle Points. NeurIPS Yingxiang Yang, Bo Dai, Negar Kiyavash, Niao He
2018	A*	`conf`	SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation. ICML Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song
2018	A*	`conf`	Structured Inference for Recurrent Hidden Semi-markov Model. IJCAI Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu
2018	—	`conf`	Syntax-Directed Variational Autoencoder for Structured Data. ICLR (Poster) Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song
2018	J	`jnl`	Syntax-Directed Variational Autoencoder for Structured Data. CoRR Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song
2018	A*	`conf`	Towards Black-box Iterative Machine Teaching. ICML Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg, Le Song
2017	J	`jnl`	Boosting the Actor with Dual Critic. CoRR Bo Dai, Albert E. Shaw, Niao He, Lihong Li, Le Song
2017	—	`conf`	Deep Hyperspherical Learning. NIPS Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song
2017	J	`jnl`	Deep Hyperspherical Learning. CoRR Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song
2017	A*	`conf`	Iterative Machine Teaching. ICML Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg, Le Song
2017	J	`jnl`	Iterative Machine Teaching. CoRR Weiyang Liu, Bo Dai, James M. Rehg, Le Song
2017	A	`conf`	Learning from Conditional Distributions via Dual Embeddings. AISTATS Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song
2017	B	`conf`	Learning from semantically dependent multi-tasks. IJCNN Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, Shandian Zhe
2017	—	`conf`	Recurrent Hidden Semi-Markov Model. ICLR (Poster) Hanjun Dai, Bo Dai, Yan-Ming Zhang, Shuang Li, Le Song
2017	J	`jnl`	Smoothed Dual Embedding Control. CoRR Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Jianshu Chen, Le Song
2017	A*	`conf`	Stochastic Generative Hashing. ICML Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song
2017	J	`jnl`	Stochastic Generative Hashing. CoRR Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song
2017	J	`jnl`	Towards Black-box Iterative Machine Teaching. CoRR Weiyang Liu, Bo Dai, Xingguo Li, James M. Rehg, Le Song
2016	J	`jnl`	A Context-Aware Framework for Reducing Bandwidth Usage of Mobile Video Chats. IEEE Trans. Multim. Xin Qi, Qing Yang, David T. Nguyen, Ge Peng, Gang Zhou, Bo Dai, Daqing Zhang, Yantao Li
2016	A*	`conf`	Discriminative Embeddings of Latent Variable Models for Structured Data. ICML Hanjun Dai, Bo Dai, Le Song
2016	J	`jnl`	Discriminative Embeddings of Latent Variable Models for Structured Data. CoRR Hanjun Dai, Bo Dai, Le Song
2016	J	`jnl`	Learning from Conditional Distributions via Dual Kernel Embeddings. CoRR Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song
2016	A	`conf`	Provable Bayesian Inference via Particle Mirror Descent. AISTATS Bo Dai, Niao He, Hanjun Dai, Le Song
2015	J	`jnl`	Scalable Bayesian Inference via Particle Mirror Descent. CoRR Bo Dai, Niao He, Hanjun Dai, Le Song
2014	J	`jnl`	Information-Theoretic Semi-Supervised Metric Learning via Entropy Regularization. Neural Comput. Gang Niu, Bo Dai, Makoto Yamada, Masashi Sugiyama
2014	A*	`conf`	Nonparametric Estimation of Multi-View Latent Variable Models. ICML Le Song, Animashree Anandkumar, Bo Dai, Bo Xie
2014	—	`conf`	Scalable Kernel Methods via Doubly Stochastic Gradients. NIPS Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song
2014	J	`jnl`	Scalable Kernel Methods via Doubly Stochastic Gradients. CoRR Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song
2014	A*	`conf`	Transductive Learning with Multi-class Volume Approximation. ICML Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama
2014	J	`jnl`	Transductive Learning with Multi-class Volume Approximation. CoRR Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama
2013	J	`jnl`	Maximum volume clustering: a new discriminative clustering approach. J. Mach. Learn. Res. Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama
2013	J	`jnl`	Nonparametric Estimation of Multi-View Latent Variable Models. CoRR Le Song, Animashree Anandkumar, Bo Dai, Bo Xie
2013	—	`conf`	Robust Low Rank Kernel Embeddings of Multivariate Distributions. NIPS Le Song, Bo Dai
2013	—	`conf`	Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning. ICML (3) Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama
2012	J	`jnl`	Information-theoretic Semi-supervised Metric Learning via Entropy Regularization CoRR Gang Niu, Bo Dai, Makoto Yamada, Masashi Sugiyama
2012	A*	`conf`	Information-theoretic Semi-supervised Metric Learning via Entropy Regularization. ICML Gang Niu, Bo Dai, Makoto Yamada, Masashi Sugiyama
2011	A	`conf`	Maximum Volume Clustering. AISTATS Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama
2010	B	`conf`	A Multiple Instance Approach for Keyword-Based Retrieval in Un-annotated Image Database. MMM Jun Jiao, Chen Shen, Bo Dai, Xuan Mo
2010	A*	`conf`	Bayesian Maximum Margin Clustering. ICDM Bo Dai, Bao-Gang Hu, Gang Niu
2010	—	`conf`	Compact Margin Machine. PAKDD (2) Bo Dai, Gang Niu
2010	C	`conf`	Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering. ACML Bo Dai, Bao-Gang Hu
2010	B	`conf`	Neural-network based regression model with prior from ranking information. IJCNN Yajun Qu, Bo Dai, Bao-Gang Hu
2010	—	`conf`	Rough Margin Based Core Vector Machine. PAKDD (1) Gang Niu, Bo Dai, Lin Shang, Yangsheng Ji