242 citations · 647 across the 20 of their papers we have counts for
5 papers · 1 filter
Best Pair Formulation & Accelerated Scheme for Non-convex Principal Component Pursuit
Aritra Dutta, Filip Hanzely, Jingwei Liang +1
The best pair problem aims to find a pair of points that minimize the distance between two disjoint sets. In this paper, we formulate the classical robust principal component analy…
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
Eduard Gorbunov, Filip Hanzely, Peter Richtárik
In this paper we introduce a unified analysis of a large family of variants of proximal stochastic gradient descent ({\tt SGD}) which so far have required different intuitions, con…
One Method to Rule Them All: Variance Reduction for Data, Parameters and Many New Methods
Filip Hanzely, Peter Richtárik
We propose a remarkably general variance-reduced method suitable for solving regularized empirical risk minimization problems with either a large number of training examples, or a…
A Privacy Preserving Randomized Gossip Algorithm via Controlled Noise Insertion
Filip Hanzely, Jakub Konečný, Nicolas Loizou +2
In this work we present a randomized gossip algorithm for solving the average consensus problem while at the same time protecting the information about the initial private values s…
99% of Distributed Optimization is a Waste of Time: The Issue and How to Fix it
Konstantin Mishchenko, Filip Hanzely, Peter Richtárik
Many popular distributed optimization methods for training machine learning models fit the following template: a local gradient estimate is computed independently by each worker, t…