4 papers
Where Have All the Kaczmarz Iterates Gone?
El Houcine Bergou, Soumia Boucherouite, Aritra Dutta +2
The randomized Kaczmarz (RK) algorithm is one of the most computationally and memory-efficient iterative algorithms for solving large-scale linear systems. However, practical appli…
Demystifying the Myths and Legends of Nonconvex Convergence of SGD
Aritra Dutta, El Houcine Bergou, Soumia Boucherouite +3
Stochastic gradient descent (SGD) and its variants are the main workhorses for solving large-scale optimization problems with nonconvex objective functions. Although the convergenc…
A Note on Randomized Kaczmarz Algorithm for Solving Doubly-Noisy Linear Systems
El Houcine Bergou, Soumia Boucherouite, Aritra Dutta +2
Large-scale linear systems, , frequently arise in practice and demand effective iterative solvers. Often, these systems are noisy due to operational errors or faulty data-col…
Minibatch Stochastic Three Points Method for Unconstrained Smooth Minimization
Soumia Boucherouite, Grigory Malinovsky, Peter Richtárik +1
In this paper, we propose a new zero order optimization method called minibatch stochastic three points (MiSTP) method to solve an unconstrained minimization problem in a setting w…