Boxiang Lyu | DeepAI

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Featured Co-authors

Michael I. Jordan
283 publications
Zhaoran Wang
121 publications
Zhuoran Yang
110 publications
Mladen Kolar
63 publications
Sanmi Koyejo
31 publications
Zhe Feng
27 publications
Shuang Qiu
26 publications
Filip Hanzely
18 publications
Raul Castro Fernandez
16 publications
Pedro Cisneros-Velarde
10 publications
Boxin Zhao
8 publications

∙ 06/05/2023

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

High-quality machine learning models are dependent on access to high-qua...

0 Boxin Zhao, et al. ∙

∙ 06/01/2023

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

We study the design of loss functions for click-through rates (CTR) to o...

0 Boxiang Lyu, et al. ∙

∙ 10/19/2022

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

We study reserve price optimization in multi-phase second price auctions...

1 Rui Ai, et al. ∙

∙ 05/31/2022

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

While parallelism has been extensively used in Reinforcement Learning (R...

0 Pedro Cisneros-Velarde, et al. ∙

∙ 05/05/2022

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

Dynamic mechanism design has garnered significant attention from both co...

1 Boxiang Lyu, et al. ∙

∙ 04/28/2022

Personalized Federated Learning with Multiple Known Clusters

We consider the problem of personalized federated learning when there ar...

0 Boxiang Lyu, et al. ∙

∙ 02/25/2022

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach

Dynamic mechanism design studies how mechanism designers should allocate...

15 Boxiang Lyu, et al. ∙

∙ 01/31/2022

L-SVRG and L-Katyusha with Adaptive Sampling

Stochastic gradient-based optimization methods, such as L-SVRG and its a...

0 Boxin Zhao, et al. ∙

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