81 citations · 264 across the 35 of their papers we have counts for
4 papers · 2 filters
Large deviations rates for stochastic gradient descent with strongly convex functions
Dragana Bajovic, Dusan Jakovetic, Soummya Kar
Recent works have shown that high probability metrics with stochastic gradient descent (SGD) exhibit informativeness and in some cases advantage over the commonly adopted mean-squa…
A One-shot Framework for Distributed Clustered Learning in Heterogeneous Environments
Aleksandar Armacki, Dragana Bajovic, Dusan Jakovetic +1
The paper proposes a family of communication efficient methods for distributed learning in heterogeneous environments in which users obtain data from one of different distribut…
Personalized Federated Learning via Convex Clustering
Aleksandar Armacki, Dragana Bajovic, Dusan Jakovetic +1
We propose a parametric family of algorithms for personalized federated learning with locally convex user costs. The proposed framework is based on a generalization of convex clust…
Gradient Based Clustering
Aleksandar Armacki, Dragana Bajovic, Dusan Jakovetic +1
We propose a general approach for distance based clustering, using the gradient of the cost function that measures clustering quality with respect to cluster assignments and cluste…