Boxiang Lyu

According to our database, Boxiang Lyu authored at least 12 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An Instrumental Value for Data Production and its Application to Data Pricing.

Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Haifeng Xu

CoRR, 2024

Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning.

Shuang Qiu, Dake Zhang, Rui Yang, Boxiang Lyu, Tong Zhang

CoRR, 2024

Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning.

Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

L-SVRG and L-Katyusha with Adaptive Sampling.

Boxin Zhao, Boxiang Lyu, Mladen Kolar

Trans. Mach. Learn. Res., 2023

Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm.

Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar

Proceedings of the International Conference on Machine Learning, 2023

Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions.

Boxiang Lyu, Zhe Feng, Zachary Robertson, Sanmi Koyejo

Proceedings of the International Conference on Machine Learning, 2023

One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning.

Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design.

Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan

CoRR, 2022

One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning.

Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar

CoRR, 2022

Personalized Federated Learning with Multiple Known Clusters.

Boxiang Lyu, Filip Hanzely, Mladen Kolar

CoRR, 2022

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach.

Boxiang Lyu, Qinglin Meng, Shuang Qiu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan

CoRR, 2022

Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning.

Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang

Proceedings of the International Conference on Machine Learning, 2022