Byzantine-Robust Decentralized Federated Learning
Minghong Fang, Zifan Zhang, et al.
CCS 2024
A recommendation system tracks past actions of a group of users to make recommendations to individual members of the group. The growth of computer-mediated marketing and commerce has led to increased interest in such systems. We introduce a simple analytical framework for recommendation systems, including a basis for defining the utility of such a system. We perform probabilistic analyses of algorithms within this framework. These analyses yield insights into how much utility can be derived from knowledge of past user actions.
Minghong Fang, Zifan Zhang, et al.
CCS 2024
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Guo-Jun Qi, Charu Aggarwal, et al.
IEEE TPAMI
Heinz Koeppl, Marc Hafner, et al.
BMC Bioinformatics