2 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
Incentivizing Truthful Collaboration in Heterogeneous Federated Learning
Dimitar Chakarov, Nikita Tsoy, Kristian Minchev +1
Federated learning (FL) is a distributed collaborative learning method, where multiple clients learn together by sharing gradient updates instead of raw data. However, it is well-k…
Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
Nikita Tsoy, Nikola Konstantinov
Simplicity bias, the propensity of deep models to over-rely on simple features, has been identified as a potential reason for limited out-of-distribution generalization of neural n…
Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains
Nikita Tsoy, Anna Mihalkova, Teodora Todorova +1
Cross-silo federated learning (FL) allows data owners to train accurate machine learning models by benefiting from each others private datasets. Unfortunately, the model accuracy b…