3 citations · 9 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
Federated Transfer Learning with Differential Privacy
Mengchu Li, Ye Tian, Yang Feng +1
Federated learning has emerged as a powerful framework for analysing distributed data, yet two challenges remain pivotal: heterogeneity across sites and privacy of local data. In t…
Robust mean change point testing in high-dimensional data with heavy tails
Mengchu Li, Yudong Chen, Tengyao Wang +1
We study mean change point testing problems for high-dimensional data, with exponentially- or polynomially-decaying tails. In each case, depending on the -norm of the mean…
Network change point localisation under local differential privacy
Mengchu Li, Thomas B. Berrett, Yi Yu
Network data are ubiquitous in our daily life, containing rich but often sensitive information. In this paper, we expand the current static analysis of privatised networks to a dyn…
On robustness and local differential privacy
Mengchu Li, Thomas B. Berrett, Yi Yu
It is of soaring demand to develop statistical analysis tools that are robust against contamination as well as preserving individual data owners' privacy. In spite of the fact that…
Adversarially robust change point detection
Mengchu Li, Yi Yu
Change point detection is becoming increasingly popular in many application areas. On one hand, most of the theoretically-justified methods are investigated in an ideal setting wit…