Publications

Reinforcement Learning

• Regret Bounds for Information-Directed Reinforcement Learning
  Botao Hao, Tor Lattimore
  NeurIPS 2022. [arXiv]

• Confident Least Square Value Iteration with Local Access to a Simulator
  Botao Hao, Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvári
  AISTATS 2022. [Proceedings]

• Efficient Local Planning with Linear Function Approximation
  Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvári
  ALT 2022. [arXiv]

• Bootstrapping Fitted Q-Evaluation for Off-Policy Inference
  Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang
  ICML 2021. [arXiv]

• Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
  Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang
  ICML 2021. [arXiv]

• Online Sparse Reinforcement Learning
  Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang
  AISTATS 2021. [arXiv] [poster]

• Adaptive Approximate Policy Iteration
  Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári
  AISTATS 2021. [arXiv] [poster]

Online Learning and Bandits

• Leveraging Demonstrations to Improve Online Learning: Quality Matters
  Botao Hao, Rahul Jain, Tor Lattimore, Benjamin Van Roy, Zheng Wen
  Submitted. [arXiv]

• Contextual Information-Directed Sampling
  Botao Hao, Tor Lattimore, Chao Qin
  ICML 2022. [arXiv]

• Information Directed Sampling for Sparse Linear Bandits
  Botao Hao, Tor Lattimore, Wei Deng
  NeurIPS 2021 (spotlight). [Proceedings] [slides]

• Bandit Phase Retrieval
  Tor Lattimore, Botao Hao
  NeurIPS 2021. [arXiv]

• High-Dimensional Sparse Linear Bandits
  Botao Hao, Tor Lattimore, Mengdi Wang
  NeurIPS 2020. [arXiv] [slides] [poster]

• Adaptive Exploration in Linear Contextual Bandit
  Botao Hao, Tor Lattimore, Csaba Szepesvári
  AISTATS 2020. [arXiv] [slides]

• Bootstrapping Upper Confidence Bound
  Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng
  NeurIPS 2019. [arXiv] [poster]

Statistical Machine Learning

• Sparse Tensor Additive Regression
  Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang, Jian Yang, Will Wei Sun
  Journal of Machine Learning Research (2021). [arXiv]

• Sparse and Low-rank Tensor Estimation via Cubic Sketchings
  Botao Hao, Anru Zhang, Guang Cheng
  IEEE Transactions on Information Theory (2020). [arXiv] [slides]
  Accepted in part to AISTATS 2020.

• Simultaneous Clustering and Estimation of Heterogeneous Graphical Models
  Botao Hao, Will Wei Sun, Yufeng Liu, Guang Cheng
  Journal of Machine Learning Research (2018). [pdf] [slides]

Bayesian Learning

• The Neural Testbed: Evaluating Predictive Distributions
  Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy
  NeurIPS 2022. [arXiv]

• Interacting Contour Stochastic Gradient Langevin Dynamics
  Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
  ICLR 2022. [arXiv]

• Nonparametric Bayesian Aggregation for Massive Data
  Zuofeng Shang, Botao Hao, Guang Cheng
  Journal of Machine Learning Research (2019). [pdf]