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Botao Hao

According to our database¹, Botao Hao authored at least 32 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

On csauthors.net:

Bibliography

2024

Efficient Exploration for LLMs.

[BibT_eX]

[DOI]

Vikranth Dwaracherla

,

Seyed Mohammad Asghari

,

,

Benjamin Van Roy

CoRR, 2024

2023

Efficient Online Learning with Offline Datasets for Infinite Horizon MDPs: A Bayesian Approach.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2023

Sequential Best-Arm Identification with Application to Brain-Computer Interface.

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2023

Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2023

Sample Efficient Deep Reinforcement Learning via Local Planning.

[BibT_eX]

[DOI]

,

Sridhar Thiagarajan

,

,

Nived Rajaraman

,

,

Csaba Szepesvári

CoRR, 2023

Leveraging Demonstrations to Improve Online Learning: Quality Matters.

[BibT_eX]

[DOI]

,

,

,

Benjamin Van Roy

,

Proceedings of the International Conference on Machine Learning, 2023

2022

The Neural Testbed: Evaluating Joint Predictions.

[BibT_eX]

[DOI]

,

,

Seyed Mohammad Asghari

,

Vikranth Dwaracherla

,

,

Morteza Ibrahimi

,

Dieterich Lawson

,

,

Brendan O'Donoghue

,

Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Regret Bounds for Information-Directed Reinforcement Learning.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Contextual Information-Directed Sampling.

[BibT_eX]

[DOI]

,

,

Proceedings of the International Conference on Machine Learning, 2022

Interacting Contour Stochastic Gradient Langevin Dynamics.

[BibT_eX]

[DOI]

,

,

,

,

Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient local planning with linear function approximation.

[BibT_eX]

[DOI]

,

,

Yasin Abbasi-Yadkori

,

,

Csaba Szepesvári

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Confident Least Square Value Iteration with Local Access to a Simulator.

[BibT_eX]

[DOI]

,

,

,

Yasin Abbasi-Yadkori

,

Csaba Szepesvári

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Sparse Tensor Additive Regression.

[BibT_eX]

[DOI]

,

,

,

,

,

J. Mach. Learn. Res., 2021

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?

[BibT_eX]

[DOI]

,

,

Seyed Mohammad Asghari

,

Vikranth Dwaracherla

,

,

Morteza Ibrahimi

,

Dieterich Lawson

,

,

Brendan O'Donoghue

,

Benjamin Van Roy

CoRR, 2021

Optimization Issues in KL-Constrained Approximate Policy Iteration.

[BibT_eX]

[DOI]

,

,

Yasin Abbasi-Yadkori

,

Dale Schuurmans

,

Csaba Szepesvári

CoRR, 2021

Bootstrapping Statistical Inference for Off-Policy Evaluation.

[BibT_eX]

[DOI]

,

,

,

,

Csaba Szepesvári

,

CoRR, 2021

Bandit Phase Retrieval.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Information Directed Sampling for Sparse Linear Bandits.

[BibT_eX]

[DOI]

,

,

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bootstrapping Fitted Q-Evaluation for Off-Policy Inference.

[BibT_eX]

[DOI]

,

,

,

,

Csaba Szepesvári

,

Proceedings of the 38th International Conference on Machine Learning, 2021

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient.

[BibT_eX]

[DOI]

,

,

,

Csaba Szepesvári

,

Proceedings of the 38th International Conference on Machine Learning, 2021

Online Sparse Reinforcement Learning.

[BibT_eX]

[DOI]

,

,

Csaba Szepesvári

,

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Adaptive Approximate Policy Iteration.

[BibT_eX]

[DOI]

,

,

Yasin Abbasi-Yadkori

,

,

Csaba Szepesvári

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Sparse and Low-Rank Tensor Estimation via Cubic Sketchings.

[BibT_eX]

[DOI]

,

,

IEEE Trans. Inf. Theory, 2020

Low-rank Tensor Bandits.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2020

Residual Bootstrap Exploration for Bandit Algorithms.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2020

Provably Efficient Adaptive Approximate Policy Iteration.

[BibT_eX]

[DOI]

,

,

Yasin Abbasi-Yadkori

,

,

Csaba Szepesvári

CoRR, 2020

High-Dimensional Sparse Linear Bandits.

[BibT_eX]

[DOI]

,

,

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adaptive Exploration in Linear Contextual Bandit.

[BibT_eX]

[DOI]

,

,

Csaba Szepesvári

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Nonparametric Bayesian Aggregation for Massive Data.

[BibT_eX]

[DOI]

,

,

J. Mach. Learn. Res., 2019

Bootstrapping Upper Confidence Bound.

[BibT_eX]

[DOI]

,

Yasin Abbasi-Yadkori

,

,

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

CML-IOT 2019: the first workshop on continual and multimodal learning for internet of things.

[BibT_eX]

[DOI]

,

,

,

,

Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019

2017

Simultaneous Clustering and Estimation of Heterogeneous Graphical Models.

[BibT_eX]

[DOI]

,

,

,

J. Mach. Learn. Res., 2017

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