Showing cs.IRShow all
3 papers · 1 filter
cs.IR2025
Unlearning for Federated Online Learning to Rank: A Reproducibility Study
Yiling Tao, Shuyi Wang, Jiaxi Yang +1
This paper reports on findings from a comparative study on the effectiveness and efficiency of federated unlearning strategies within Federated Online Learning to Rank (FOLTR), wit…
cs.IR2023
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems
Shuyi Wang, Guido Zuccon
Federated online learning to rank (FOLTR) aims to preserve user privacy by not sharing their searchable data and search interactions, while guaranteeing high search effectiveness,…
cs.IR2022
Is Non-IID Data a Threat in Federated Online Learning to Rank?
Shuyi Wang, Guido Zuccon
In this perspective paper we study the effect of non independent and identically distributed (non-IID) data on federated online learning to rank (FOLTR) and chart directions for fu…