Simultaneous Clustering and Estimation of Heterogeneous Graphical Models. - Botao Hao; Will Wei Sun; Yufeng Liu; Guang Cheng 003 (J. Mach. Learn. Res., 2017)

CML-IOT 2019: the first workshop on continual and multimodal learning for internet of things. - Tong Yu 001; Shijia Pan; Susu Xu; Yilin Shen; Botao Hao (UbiComp/ISWC Adjunct, 2019)

Bootstrapping Upper Confidence Bound. - Botao Hao; Yasin Abbasi-Yadkori; Zheng Wen 002; Guang Cheng 003 (NeurIPS, 2019)

Nonparametric Bayesian Aggregation for Massive Data. - Zuofeng Shang; Botao Hao; Guang Cheng 003 (J. Mach. Learn. Res., 2019)

Adaptive Exploration in Linear Contextual Bandit. - Botao Hao; Tor Lattimore; Csaba Szepesvári (AISTATS, 2020)

High-Dimensional Sparse Linear Bandits. - Botao Hao; Tor Lattimore; Mengdi Wang (NeurIPS, 2020)

Provably Efficient Adaptive Approximate Policy Iteration. - Botao Hao; Nevena Lazic; Yasin Abbasi-Yadkori; Pooria Joulani; Csaba Szepesvári (CoRR, 2020)

Residual Bootstrap Exploration for Bandit Algorithms. - Chi-Hua Wang; Yang Yu 052; Botao Hao; Guang Cheng 003 (CoRR, 2020)

Low-rank Tensor Bandits. - Botao Hao; Jie Zhou; Zheng Wen 002; Will Wei Sun (CoRR, 2020)

Sparse and Low-Rank Tensor Estimation via Cubic Sketchings. - Botao Hao; Anru Zhang; Guang Cheng 003 (IEEE Trans. Inf. Theory, 2020)

Adaptive Approximate Policy Iteration. - Botao Hao; Nevena Lazic; Yasin Abbasi-Yadkori; Pooria Joulani; Csaba Szepesvári (AISTATS, 2021)

Online Sparse Reinforcement Learning. - Botao Hao; Tor Lattimore; Csaba Szepesvári; Mengdi Wang (AISTATS, 2021)

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. - Botao Hao; Yaqi Duan; Tor Lattimore; Csaba Szepesvári; Mengdi Wang (ICML, 2021)

Bootstrapping Fitted Q-Evaluation for Off-Policy Inference. - Botao Hao; Xiang Ji; Yaqi Duan; Hao Lu; Csaba Szepesvári; Mengdi Wang (ICML, 2021)

Information Directed Sampling for Sparse Linear Bandits. - Botao Hao; Tor Lattimore; Wei Deng 002 (NeurIPS, 2021)

Bandit Phase Retrieval. - Tor Lattimore; Botao Hao (NeurIPS, 2021)

Bootstrapping Statistical Inference for Off-Policy Evaluation. - Botao Hao; Xiang Ji; Yaqi Duan; Hao Lu; Csaba Szepesvári; Mengdi Wang (CoRR, 2021)

Optimization Issues in KL-Constrained Approximate Policy Iteration. - Nevena Lazic; Botao Hao; Yasin Abbasi-Yadkori; Dale Schuurmans; Csaba Szepesvári (CoRR, 2021)

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Botao Hao; Morteza Ibrahimi; Dieterich Lawson; Xiuyuan Lu; Brendan O'Donoghue; Benjamin Van Roy (CoRR, 2021)

Sparse Tensor Additive Regression. - Botao Hao; Boxiang Wang; Pengyuan Wang 001; Jingfei Zhang; Jian Yang 002; Will Wei Sun (J. Mach. Learn. Res., 2021)

Confident Least Square Value Iteration with Local Access to a Simulator. - Botao Hao; Nevena Lazic; Dong Yin; Yasin Abbasi-Yadkori; Csaba Szepesvári (AISTATS, 2022)

Efficient local planning with linear function approximation. - Dong Yin; Botao Hao; Yasin Abbasi-Yadkori; Nevena Lazic; Csaba Szepesvári (ALT, 2022)

Interacting Contour Stochastic Gradient Langevin Dynamics. - Wei Deng 002; Siqi Liang 005; Botao Hao; Guang Lin 001; Faming Liang (ICLR, 2022)

Contextual Information-Directed Sampling. - Botao Hao; Tor Lattimore; Chao Qin (ICML, 2022)

Regret Bounds for Information-Directed Reinforcement Learning. - Botao Hao; Tor Lattimore (NeurIPS, 2022)

The Neural Testbed: Evaluating Joint Predictions. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Xiuyuan Lu; Morteza Ibrahimi; Dieterich Lawson; Botao Hao; Brendan O'Donoghue; Benjamin Van Roy (NeurIPS, 2022)

Leveraging Demonstrations to Improve Online Learning: Quality Matters. - Botao Hao; Rahul Jain 002; Tor Lattimore; Benjamin Van Roy; Zheng Wen 002 (ICML, 2023)

Sample Efficient Deep Reinforcement Learning via Local Planning. - Dong Yin; Sridhar Thiagarajan; Nevena Lazic; Nived Rajaraman; Botao Hao; Csaba Szepesvári (CoRR, 2023)

Sequential Best-Arm Identification with Application to Brain-Computer Interface. - Xin Zhou; Botao Hao; Jian Kang; Tor Lattimore; Lexin Li (CoRR, 2023)

Efficient Online Learning with Offline Datasets for Infinite Horizon MDPs: A Bayesian Approach. - Dengwang Tang; Rahul Jain 002; Botao Hao; Zheng Wen 002 (CoRR, 2023)

Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale. - Botao Hao; Rahul Jain 002; Dengwang Tang; Zheng Wen 002 (Trans. Mach. Learn. Res., 2023)

Efficient Exploration for LLMs. - Vikranth Dwaracherla; Seyed Mohammad Asghari; Botao Hao; Benjamin Van Roy (ICML, 2024)

OpenAI o1 System Card. - Aaron Jaech; Adam Kalai; Adam Lerer; Adam Richardson; Ahmed El-Kishky; Aiden Low; Alec Helyar; Aleksander Madry; Alex Beutel; Alex Carney; Alex Iftimie; Alex Karpenko; et al. (CoRR, 2024)

Sequential Best-Arm Identification with Application to P300 Speller. - Xin Zhou; Botao Hao; Tor Lattimore; Jian Kang; Lexin Li (Trans. Mach. Learn. Res., 2024)