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2020 – today
- 2024
[c5]Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang:
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. ICML 2024- [i10]Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang:
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. CoRR abs/2407.07631 (2024) - [i9]Shuang Qiu, Dake Zhang, Rui Yang, Boxiang Lyu, Tong Zhang:
Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning. CoRR abs/2407.17466 (2024) - 2023
- [j1]Boxin Zhao, Boxiang Lyu, Mladen Kolar:
L-SVRG and L-Katyusha with Adaptive Sampling. Trans. Mach. Learn. Res. 2023 (2023) - [c4]Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar:
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning. AISTATS 2023: 1965-2001 - [c3]Boxiang Lyu, Zhe Feng, Zachary Robertson, Sanmi Koyejo:
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions. ICML 2023: 23239-23263 - [c2]Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar:
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm. ICML 2023: 42081-42097 - [i8]Boxiang Lyu, Zhe Feng, Zachary Robertson, Sanmi Koyejo:
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions. CoRR abs/2306.01799 (2023) - [i7]Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar:
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm. CoRR abs/2306.02543 (2023) - 2022
- [c1]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. ICML 2022: 14601-14638 - [i6]Boxin Zhao, Boxiang Lyu, Mladen Kolar:
L-SVRG and L-Katyusha with Adaptive Sampling. CoRR abs/2201.13387 (2022) - [i5]Boxiang Lyu, Qinglin Meng, Shuang Qiu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan:
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach. CoRR abs/2202.12797 (2022) - [i4]Boxiang Lyu, Filip Hanzely, Mladen Kolar:
Personalized Federated Learning with Multiple Known Clusters. CoRR abs/2204.13619 (2022) - [i3]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. CoRR abs/2205.02450 (2022) - [i2]Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar:
One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning. CoRR abs/2205.15891 (2022) - [i1]Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan:
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design. CoRR abs/2210.10278 (2022)
Coauthor Index
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