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3 papers · Latest:

Statistical Machine Learning

Adaptive multi-fidelity optimization with fast learning rates

Kometo is a new adaptive multi-fidelity optimization algorithm that achieves fast learning rates and improves upon prior guarantees without needing problem-specific knowledge.

2604.16239
Machine Learning

The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback

New algorithms achieve optimal last-iterate convergence rates for uncoupled learning in zero-sum games with bandit feedback, despite inherent challenges.

2604.16087
Machine Learning

Optimal last-iterate convergence in matrix games with bandit feedback using the log-barrier

This paper uses log-barrier regularization to achieve optimal O-tilde(t^{-1/4}) last-iterate convergence in zero-sum matrix games.

2604.15242

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