3 citations · 9 across the 8 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
stat.ML2026
Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms
Ye Tian, Mengchu Li, Marco Avella Medina
Integrating information across related tasks can improve estimation and prediction in transfer, multi-task, and federated learning, but contamination and heterogeneity make robust…
math.ST2026
Online change point detection under heavy-tailedness and contamination
Edwin Yiu Nam Tang, Yudong Chen, Mengchu Li +1
We study an online version of the robust mean change point detection problem under a dynamic Huber contamination model with arbitrary contamination distribution and inlier distribu…
cs.CL2026
Segmenting Human-LLM Co-authored Text via Change Point Detection
Mengchu Li, Jin Zhu, Jinglai Li +1
The rise of large language models (LLMs) has created an urgent need to distinguish between human-written and LLM-generated text to ensure authenticity and societal trust. Existing…