Assistant Professor of Biostatistics & Bioinformatics
My research is centered around Machine Learning, with broad interests in the areas of Artificial Intelligence, Data Science, Optimization, Reinforcement Learning, High Dimensional Statistics, and their applications to real-world problems including Bioinformatics and Healthcare. My research goal is to develop computationally- and data-efficient machine learning algorithms with both strong empirical performance and theoretical guarantees.
Appointments and Affiliations
- Assistant Professor of Biostatistics & Bioinformatics
- Assistant Professor of Computer Science
- Assistant Professor in the Department of Electrical and Computer Engineering
Contact Information
- Email Address: pan.xu@duke.edu
- Websites:
Education
- Ph.D. University of California, Los Angeles, 2021
Research Interests
Artificial Intelligence, Data Science, Optimization, Reinforcement Learning, and High Dimensional Statistics
Courses Taught
- COMPSCI 391: Independent Study
- BIOSTAT 825: Foundation of Reinforcement Learning
Representative Publications
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.
- Ren, Xuanfei, Tianyuan Jin, and Pan Xu. “Optimal Batched Linear Bandits,” June 6, 2024.
- Lopez, Velma K., Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O’Dea, Madeline Adee, Turgay Ayer, et al. “Challenges of COVID-19 Case Forecasting in the US, 2020-2021.” PLoS Comput Biol 20, no. 5 (May 2024): e1011200. https://doi.org/10.1371/journal.pcbi.1011200.
- Hsu, Hao-Lun, Weixin Wang, Miroslav Pajic, and Pan Xu. “Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning,” April 16, 2024.
- Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the AAAI Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
- Liu, Zhishuai, and Pan Xu. “Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning,” March 14, 2024.