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math.OC2026
Optimal Rates for Federated Variational Inequalities under different relaxations of bounded variance assumption
Kirill Novoselov, Yuriy Dorn, Darina Dvinskikh +1
We study how interpolation affects local steps and parallel sampling in monotone variational inequalities (VIs), with workers, oracle calls per worker per round, and ro…
math.OC2026
Asking the Crowd the Right Question: Bias-Cancelling Weights for Federated Learning
Ilya Kuruzov, Dmitrii Vishovan, Kirill Novoselov +3
A federated objective is a weighted sum of client risks, and the weights are almost always fixed in advance. We treat them instead as the only instrument of a wisdom-of-crowds mech…
math.OC2026
Higher-Order vs. Quadratic Binary Optimization: Which Is Better for Probability Optimization with Tensor Sampling?
Hadi Salloum, Kirill Novoselov, Aleksandr Pochtarev +1
This article explores the comparative strengths of Higher-Order Unconstrained Binary Optimization (HUBO) and Quadratic Unconstrained Binary Optimization (QUBO) models in the contex…