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20182022
most citedEfficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces

5 citations · 10 across the 15 of their papers we have counts for

collaborators

25 papers

physics.plasm-ph2022

A Note on Optimal Tokamak Control for Fusion Power Simulation

M. Holst, V. Kungurtsev, S. Mukherjee

The Tokamak device is the most promising candidate for producing sustainable electric power by nuclear fusion. It is a torus-shaped device that confines plasma by a strong magnetic…

stat.ML2022

Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling

Jacopo Guidolin, Vyacheslav Kungurtsev, Ondřej Kuželka

Bayesian methods of sampling from a posterior distribution are becoming increasingly popular due to their ability to precisely display the uncertainty of a model fit. Classical met…

cs.LG20225 cited

Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces

Saeed Vahidian, Mahdi Morafah, Weijia Wang +4

Clustered federated learning (FL) has been shown to produce promising results by grouping clients into clusters. This is especially effective in scenarios where separate groups of…

cs.LG2022

Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGD

Bapi Chatterjee, Vyacheslav Kungurtsev, Dan Alistarh

Powered by the simplicity of lock-free asynchrony, Hogwilld! is a go-to approach to parallelize SGD over a shared-memory setting. Despite its popularity and concomitant extensions,…

math.OC2022

Retraction based Direct Search Methods for Derivative Free Riemannian Optimization

Vyacheslav Kungurtsev, Francesco Rinaldi, Damiano Zeffiro

Direct search methods represent a robust and reliable class of algorithms for solving black-box optimization problems. In this paper, we explore the application of those strategies…

math.OC2021

Decentralized Asynchronous Non-convex Stochastic Optimization on Directed Graphs

Vyacheslav Kungurtsev, Mahdi Morafah, Tara Javidi +1

Distributed Optimization is an increasingly important subject area with the rise of multi-agent control and optimization. We consider a decentralized stochastic optimization proble…