Quantum Acceleration For Frontier AI: Does It Cut The Cost Of Training?

Where, exactly, could quantum hardware reduce end-to-end training cost rather than merely improve asymptotic complexity on a ...
IEEE

Byzantine-robust Distributed Stochastic Non-convex Optimization in Adversarial Environments over Unbalanced Networks

Abstract: This paper focuses on a Byzantine-robust distributed stochastic non-convex optimization problem with smooth local cost functions over unbalanced networks. In particular, the nodes in a ...
IEEE

Convergence Analysis of EXTRA in Non-Convex Distributed Optimization

Abstract: Optimization problems involving the minimization of a finite sum of smooth, possibly non-convex functions arise in numerous applications. To achieve a consensus solution over a network, ...
GitHub

EPFL Course - Optimization for Machine Learning - CS-439

This course teaches an overview of modern mathematical optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be ...
Scientific Research Publishing

A Comparative Study of Optimization Techniques on the Rosenbrock Function ()

1 Department of Mathematics, University of Ndjamena, Ndjamena, Tchad. 2 Department of Mathematics and Computer Science, University of Cheikh. A. Diop, Dakar, Senegal. In the evolving landscape of ...