1 citations · 2 across the 25 of their papers we have counts for
9 papers · 2 filters
Pessimistic Minimax Learning for Public-Private Information Games under Unilateral Coverage
Shuze Daniel Liu, Claire Chen, Jiuqi Wang +1
We study offline learning in two-player zero-sum contextual games with public and private information, motivated by strategic settings such as auctions and negotiations with privat…
Minimax-Optimal Online Contract Design with Unrestricted Bounded Contracts
Rui Ai, David Simchi-Levi, Han Zhong
We study repeated contract design when a principal observes outcomes but not the actions that generate them. The principal may use any bounded outcome-contingent payment vector, an…
Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback
Haichen Hu, Yuheng Zhang, David Simchi-Levi
Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a smaller student. Direct imitation, however, can also transfer the teacher's sys…
Sharp Structure-Agnostic Minimax Risk for Partial Linear Models
Haichen Hu, David Simchi-Levi
We characterize the sharp structure-agnostic minimax risk for coefficient estimation in the partial linear model when the outcome and treatment nuisances are learned by two distinc…
OR-Transformer: Scaling Real-Time Decision-Making to 1,000 Items
Shuze Daniel Liu, David Simchi-Levi, Claire Chen +2
Modern supply chain operations can require coordinating replenishment across thousands of heterogeneous items under correlated stochastic demand, heterogeneous lead times, and shar…
Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles
Haichen Hu, David Simchi-Levi
Stochastic nonconvex optimization is central to training deep networks and LLMs in modern machine learning. We give a black-box reduction from stochastic nonconvex optimization to…
Strategic Bargaining in Multi-Buyer Markets: Reinforcement Learning from Verifiable Rewards for LLM Negotiations
Shuze Daniel Liu, Claire Chen, Jiabao Sean Xiao +2
Negotiation is a fundamental strategic interaction in management science, characterized by agents attempting to reach agreements while protecting private information, such as reser…
Model-Based Reinforcement Learning with Double Oracle Efficiency in Policy Optimization and Offline Estimation
Haichen Hu, Jian Qian, David Simchi-Levi
Reinforcement learning (RL) in large environments often suffers from severe computational bottlenecks, as conventional regret minimization algorithms require repeated, costly calls…
Interleaved Resampling and Refitting: Data and Compute-Efficient Evaluation of Black-Box Predictors
Haichen Hu, David Simchi-Levi
We study the problem of evaluating the excess risk of large-scale empirical risk minimization under the square loss. Leveraging the idea of wild refitting and resampling, we assume…