3 papers
cs.LG2026
Online Learning with Gradient-Variation Interval Regret
Yan-Feng Xie, Shuche Wang, Peng Zhao +1
This paper investigates non-stationary online learning using the metric of interval regret, which requires an online algorithm to perform well over every time interval. We propose…
cs.LG2026
Robust Length Prediction: A Perspective from Heavy-Tailed Prompt-Conditioned Distributions
Jing Wang, Yu-Yang Qian, Ke Xue +3
Output-length prediction is important for efficient LLM serving, as it directly affects batching, memory reservation, and scheduling. For prompt-only length prediction, most existi…
cs.LG2025
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang, Yu-Jie Zhang, Peng Zhao +1
We study the stochastic linear bandits with heavy-tailed noise. Two principled strategies for handling heavy-tailed noise, truncation and median-of-means, have been introduced to h…