11 papers
Accelerating Min-Max Optimization via Power-Law Stepsizes
Yue Wu, Weiqiang Zheng, Yang Cai +1
We revisit the convergence guarantees of the Extragradient (EG) method for unconstrained biaffine min-max optimization. It is known that EG with a fixed stepsize achieves a $Î(T^{…
Last-Iterate Convergence of Anchored Gradient Descent
Yang Cai, Weiqiang Zheng
We study the monotone inclusion problem , where is monotone and Lipschitz, and is maximally monotone, a framework that encompasses monotone variational ineq…
A New Lower Bound for the Random Offerer Mechanism in Bilateral Trade using AI-Guided Evolutionary Search
Yang Cai, Vineet Gupta, Zun Li +1
The celebrated Myerson--Satterthwaite theorem shows that in bilateral trade, no mechanism can be simultaneously fully efficient, Bayesian incentive compatible (BIC), and budget bal…
Is Online Linear Optimization Sufficient for Strategic Robustness?
Yang Cai, Haipeng Luo, Chen-Yu Wei +1
We consider bidding in repeated Bayesian first-price auctions. Bidding algorithms that achieve optimal regret have been extensively studied, but their strategic robustness to the s…
Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling
Yang Cai, Weiqiang Zheng
Aligning large language models (LLMs) to serve users with heterogeneous and potentially conflicting preferences is a central challenge for personalized and trustworthy AI. We forma…
From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications
Yang Cai, Haipeng Luo, Chen-Yu Wei +1
The convergence of online learning algorithms in games under self-play is a fundamental question in game theory and machine learning. Among various notions of convergence, last-ite…