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Journal Articles
- 2023
[j5]Botao Hao, Rahul Jain, Dengwang Tang, Zheng Wen:
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale. Trans. Mach. Learn. Res. 2023 (2023)- 2021
- [j4]Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang, Jian Yang, Will Wei Sun:
Sparse Tensor Additive Regression. J. Mach. Learn. Res. 22: 64:1-64:43 (2021) - 2020
- [j3]Botao Hao, Anru Zhang
, Guang Cheng:
Sparse and Low-Rank Tensor Estimation via Cubic Sketchings. IEEE Trans. Inf. Theory 66(9): 5927-5964 (2020) - 2019
- [j2]Zuofeng Shang, Botao Hao, Guang Cheng:
Nonparametric Bayesian Aggregation for Massive Data. J. Mach. Learn. Res. 20: 140:1-140:81 (2019) - 2017
- [j1]Botao Hao, Will Wei Sun, Yufeng Liu, Guang Cheng:
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models. J. Mach. Learn. Res. 18: 217:1-217:58 (2017)
Conference and Workshop Papers
- 2024
- [c19]Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy:
Efficient Exploration for LLMs. ICML 2024 - 2023
- [c18]Botao Hao, Rahul Jain, Tor Lattimore, Benjamin Van Roy, Zheng Wen:
Leveraging Demonstrations to Improve Online Learning: Quality Matters. ICML 2023: 12527-12545 - 2022
- [c17]Botao Hao, Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvári:
Confident Least Square Value Iteration with Local Access to a Simulator. AISTATS 2022: 2420-2435 - [c16]Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvári:
Efficient local planning with linear function approximation. ALT 2022: 1165-1192 - [c15]Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang:
Interacting Contour Stochastic Gradient Langevin Dynamics. ICLR 2022 - [c14]Botao Hao, Tor Lattimore, Chao Qin:
Contextual Information-Directed Sampling. ICML 2022: 8446-8464 - [c13]Botao Hao, Tor Lattimore:
Regret Bounds for Information-Directed Reinforcement Learning. NeurIPS 2022 - [c12]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 - 2021
- [c11]Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Online Sparse Reinforcement Learning. AISTATS 2021: 316-324 - [c10]Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári:
Adaptive Approximate Policy Iteration. AISTATS 2021: 523-531 - [c9]Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. ICML 2021: 4063-4073 - [c8]Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang:
Bootstrapping Fitted Q-Evaluation for Off-Policy Inference. ICML 2021: 4074-4084 - [c7]Botao Hao, Tor Lattimore, Wei Deng:
Information Directed Sampling for Sparse Linear Bandits. NeurIPS 2021: 16738-16750 - [c6]Tor Lattimore, Botao Hao:
Bandit Phase Retrieval. NeurIPS 2021: 18801-18811 - 2020
- [c5]Botao Hao, Anru R. Zhang, Guang Cheng:
Sparse and Low-rank Tensor Estimation via Cubic Sketchings. AISTATS 2020: 1319-1330 - [c4]Botao Hao, Tor Lattimore, Csaba Szepesvári:
Adaptive Exploration in Linear Contextual Bandit. AISTATS 2020: 3536-3545 - [c3]Botao Hao, Tor Lattimore, Mengdi Wang:
High-Dimensional Sparse Linear Bandits. NeurIPS 2020 - 2019
- [c2]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: 465-467 - [c1]Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng:
Bootstrapping Upper Confidence Bound. NeurIPS 2019: 12123-12133
Informal and Other Publications
- 2024
- [i24]Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy:
Efficient Exploration for LLMs. CoRR abs/2402.00396 (2024) - 2023
- [i23]Dong Yin, Sridhar Thiagarajan, Nevena Lazic, Nived Rajaraman, Botao Hao, Csaba Szepesvári:
Sample Efficient Deep Reinforcement Learning via Local Planning. CoRR abs/2301.12579 (2023) - [i22]Botao Hao, Rahul Jain, Tor Lattimore, Benjamin Van Roy, Zheng Wen:
Leveraging Demonstrations to Improve Online Learning: Quality Matters. CoRR abs/2302.03319 (2023) - [i21]Botao Hao, Rahul Jain, Dengwang Tang, Zheng Wen:
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale. CoRR abs/2303.11369 (2023) - [i20]Xin Zhou, Botao Hao, Jian Kang, Tor Lattimore, Lexin Li:
Sequential Best-Arm Identification with Application to Brain-Computer Interface. CoRR abs/2305.11908 (2023) - [i19]Dengwang Tang, Rahul Jain, Botao Hao, Zheng Wen:
Efficient Online Learning with Offline Datasets for Infinite Horizon MDPs: A Bayesian Approach. CoRR abs/2310.11531 (2023) - 2022
- [i18]Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang:
Interacting Contour Stochastic Gradient Langevin Dynamics. CoRR abs/2202.09867 (2022) - [i17]Botao Hao, Tor Lattimore, Chao Qin:
Contextual Information-Directed Sampling. CoRR abs/2205.10895 (2022) - [i16]Botao Hao, Tor Lattimore:
Regret Bounds for Information-Directed Reinforcement Learning. CoRR abs/2206.04640 (2022) - 2021
- [i15]Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang:
Bootstrapping Statistical Inference for Off-Policy Evaluation. CoRR abs/2102.03607 (2021) - [i14]Nevena Lazic, Botao Hao, Yasin Abbasi-Yadkori, Dale Schuurmans, Csaba Szepesvári:
Optimization Issues in KL-Constrained Approximate Policy Iteration. CoRR abs/2102.06234 (2021) - [i13]Botao Hao, Tor Lattimore, Wei Deng:
Information Directed Sampling for Sparse Linear Bandits. CoRR abs/2105.14267 (2021) - [i12]Tor Lattimore, Botao Hao:
Bandit Phase Retrieval. CoRR abs/2106.01660 (2021) - [i11]Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvári:
Efficient Local Planning with Linear Function Approximation. CoRR abs/2108.05533 (2021) - [i10]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 abs/2110.04629 (2021) - 2020
- [i9]Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári:
Provably Efficient Adaptive Approximate Policy Iteration. CoRR abs/2002.03069 (2020) - [i8]Chi-Hua Wang, Yang Yu, Botao Hao, Guang Cheng:
Residual Bootstrap Exploration for Bandit Algorithms. CoRR abs/2002.08436 (2020) - [i7]Botao Hao, Jie Zhou, Zheng Wen, Will Wei Sun:
Low-rank Tensor Bandits. CoRR abs/2007.15788 (2020) - [i6]Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Online Sparse Reinforcement Learning. CoRR abs/2011.04018 (2020) - [i5]Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. CoRR abs/2011.04019 (2020) - [i4]Botao Hao, Tor Lattimore, Mengdi Wang:
High-Dimensional Sparse Linear Bandits. CoRR abs/2011.04020 (2020) - 2019
- [i3]Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang, Jian Yang, Will Wei Sun:
Sparse Tensor Additive Regression. CoRR abs/1904.00479 (2019) - [i2]Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng:
Bootstrapping Upper Confidence Bound. CoRR abs/1906.05247 (2019) - [i1]Botao Hao, Tor Lattimore, Csaba Szepesvári:
Adaptive Exploration in Linear Contextual Bandit. CoRR abs/1910.06996 (2019)
Coauthor Index
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