Chuan Sun

Robust Bidding Strategies under Censored Feedback for Auction-Based Federated Learning.

Auction-based Federated Learning (AFL) provides a principled framework for incentivizing self-interested data owners (DOs) to participate in collaborative learning initiated by data consumers (DCs) through market mechanisms. A central challenge in AFL is to determine how a budget-constrained DC should bid for data-use...

Fisher-Based Layer-Wise Adaptive Sparsification for Efficient Pruning of Large Language Models

Personalized Federated Learning with Low-Rank Pruning-Based Adaptation for Non-IID Data

Personalized Federated Learning (pFL) has emerged as a promising paradigm, while existing approaches face 3 limitations: granularity mismatch, resource waste, and conflict aggregation. This paper presents a Personalized Federated Learning with Low-rank Pruning-based Adaptation (pFedLoPA) framework. Instead of balancing...