1 citations · 1 across the 2 of their papers we have counts for
3 papers
Prediction Limits and Koopman Closure of Geometry-Induced Soft State Abstractions
Mohit Kumar, Somayeh Kargaran
Soft state representations assign states nonnegative class weights that sum to one, but agreement with reference labels does not guarantee accurate prediction of the next weight ve…
Operator-Theoretic Framework for Gradient-Free Federated Learning
Mohit Kumar, Mathias Brucker, Alexander Valentinitsch +4
Federated learning must address heterogeneity, strict communication and computation limits, and privacy while ensuring performance. We propose an operator-theoretic framework that…
Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent
Mohit Kumar, Alexander Valentinitsch, Magdalena Fuchs +5
This paper develops a novel mathematical framework for collaborative learning by means of geometrically inspired kernel machines which includes statements on the bounds of generali…