Boxiang Lyu

According to our database1, Boxiang Lyu authored at least 11 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning.
CoRR, 2024

Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
L-SVRG and L-Katyusha with Adaptive Sampling.
Trans. Mach. Learn. Res., 2023

Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm.
Proceedings of the International Conference on Machine Learning, 2023

Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions.
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.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design.
CoRR, 2022

One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning.
CoRR, 2022

Personalized Federated Learning with Multiple Known Clusters.
CoRR, 2022

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach.
CoRR, 2022

Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022


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