Optimization
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
We further discuss the sample complexity for a desired approximation accuracy.
Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models
We derive the distortion-rate function for this setup as a linear program, and provide an efficient algorithm to compute this fundamental limit via the dual of the linear program.
Soft-Label Integration for Robust Toxicity Classification
This paper contains uncensored toxic content that might be offensive. Toxicity classification in textual content remains a significant problem.
ac4106bcfff33140de7799d03daeb8a4-Paper-Conference.pdf
Cross-V alidation (CV) is the default choice for estimate the out-of-sample performance of machine learning models.
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization
We propose adaptive, line search-free second-order methods with optimal rate of convergence for solving convex-concave min-max problems.
