Botao Hao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 47

Top Topics

Nonparametric Bayesian

Policy Iteration

Reinforcement Learning

Top Venues

Publications

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy
Efficient Exploration for LLMs. CoRR (2024)
Botao Hao, Rahul Jain, Tor Lattimore, Benjamin Van Roy, Zheng Wen
Leveraging Demonstrations to Improve Online Learning: Quality Matters. CoRR (2023)
Dengwang Tang, Rahul Jain, Botao Hao, Zheng Wen
Efficient Online Learning with Offline Datasets for Infinite Horizon MDPs: A Bayesian Approach. CoRR (2023)
Botao Hao, Rahul Jain, Dengwang Tang, Zheng Wen
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale. CoRR (2023)
Dong Yin, Sridhar Thiagarajan, Nevena Lazic, Nived Rajaraman, Botao Hao, Csaba Szepesvári
Sample Efficient Deep Reinforcement Learning via Local Planning. CoRR (2023)
Botao Hao, Rahul Jain, Dengwang Tang, Zheng Wen
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale. Trans. Mach. Learn. Res. 2023 (2023)
Xin Zhou, Botao Hao, Jian Kang, Tor Lattimore, Lexin Li
Sequential Best-Arm Identification with Application to Brain-Computer Interface. CoRR (2023)
Botao Hao, Rahul Jain, Tor Lattimore, Benjamin Van Roy, Zheng Wen
Leveraging Demonstrations to Improve Online Learning: Quality Matters. ICML (2023)
Botao Hao, Tor Lattimore
Regret Bounds for Information-Directed Reinforcement Learning. CoRR (2022)
Botao Hao, Tor Lattimore, Chao Qin
Contextual Information-Directed Sampling. CoRR (2022)
Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
Interacting Contour Stochastic Gradient Langevin Dynamics. CoRR (2022)
Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
Interacting Contour Stochastic Gradient Langevin Dynamics. ICLR (2022)
Botao Hao, Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvári
Confident Least Square Value Iteration with Local Access to a Simulator. AISTATS (2022)
Botao Hao, Tor Lattimore, Chao Qin
Contextual Information-Directed Sampling. ICML (2022)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy
The Neural Testbed: Evaluating Joint Predictions. NeurIPS (2022)
Botao Hao, Tor Lattimore
Regret Bounds for Information-Directed Reinforcement Learning. NeurIPS (2022)
Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvári
Efficient local planning with linear function approximation. ALT (2022)
Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári
Adaptive Approximate Policy Iteration. AISTATS (2021)
Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang, Jian Yang, Will Wei Sun
Sparse Tensor Additive Regression. J. Mach. Learn. Res. 22 (2021)
Tor Lattimore, Botao Hao
Bandit Phase Retrieval. CoRR (2021)
Tor Lattimore, Botao Hao
Bandit Phase Retrieval. NeurIPS (2021)
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? CoRR (2021)
Nevena Lazic, Botao Hao, Yasin Abbasi-Yadkori, Dale Schuurmans, Csaba Szepesvári
Optimization Issues in KL-Constrained Approximate Policy Iteration. CoRR (2021)
Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang
Online Sparse Reinforcement Learning. AISTATS (2021)
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang
Bootstrapping Statistical Inference for Off-Policy Evaluation. CoRR (2021)
Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvári
Efficient Local Planning with Linear Function Approximation. CoRR (2021)
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. ICML (2021)
Botao Hao, Tor Lattimore, Wei Deng
Information Directed Sampling for Sparse Linear Bandits. NeurIPS (2021)
Botao Hao, Tor Lattimore, Wei Deng
Information Directed Sampling for Sparse Linear Bandits. CoRR (2021)
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang
Bootstrapping Fitted Q-Evaluation for Off-Policy Inference. ICML (2021)
Chi-Hua Wang, Yang Yu, Botao Hao, Guang Cheng
Residual Bootstrap Exploration for Bandit Algorithms. CoRR (2020)
Botao Hao, Anru R. Zhang, Guang Cheng
Sparse and Low-rank Tensor Estimation via Cubic Sketchings. AISTATS (2020)
Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári
Provably Efficient Adaptive Approximate Policy Iteration. CoRR (2020)
Botao Hao, Anru Zhang, Guang Cheng
Sparse and Low-Rank Tensor Estimation via Cubic Sketchings. IEEE Trans. Inf. Theory 66 (9) (2020)
Botao Hao, Tor Lattimore, Mengdi Wang
High-Dimensional Sparse Linear Bandits. CoRR (2020)
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. CoRR (2020)
Botao Hao, Jie Zhou, Zheng Wen, Will Wei Sun
Low-rank Tensor Bandits. CoRR (2020)
Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang
Online Sparse Reinforcement Learning. CoRR (2020)
Botao Hao, Tor Lattimore, Csaba Szepesvári
Adaptive Exploration in Linear Contextual Bandit. AISTATS (2020)
Botao Hao, Tor Lattimore, Mengdi Wang
High-Dimensional Sparse Linear Bandits. NeurIPS (2020)
Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng
Bootstrapping Upper Confidence Bound. CoRR (2019)
Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng
Bootstrapping Upper Confidence Bound. NeurIPS (2019)
Zuofeng Shang, Botao Hao, Guang Cheng
Nonparametric Bayesian Aggregation for Massive Data. J. Mach. Learn. Res. 20 (2019)
Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang, Jian Yang, Will Wei Sun
Sparse Tensor Additive Regression. CoRR (2019)
Tong Yu, Shijia Pan, Susu Xu, Yilin Shen, Botao Hao
CML-IOT 2019: the first workshop on continual and multimodal learning for internet of things. UbiComp/ISWC Adjunct (2019)
Botao Hao, Tor Lattimore, Csaba Szepesvári
Adaptive Exploration in Linear Contextual Bandit. CoRR (2019)
Botao Hao, Will Wei Sun, Yufeng Liu, Guang Cheng
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models. J. Mach. Learn. Res. 18 (2017)