paper-with-me

홈 › Papers

Provably Accelerated Randomized Gossip Algorithms

2018-10-31 · Nicolas Loizou, Michael Rabbat, Peter Richtárik

In this work we present novel provably accelerated gossip algorithms for solving the average consensus problem. The proposed protocols are inspired from the recently developed accelerated variants of the randomized Kaczmarz method - a popular method for solving linear systems. In each gossip iteration all nodes of the network update their values but only a pair of them exchange their private information. Numerical experiments on popular wireless sensor networks showing the benefits of our protocols are also presented.

📄 PDF Abstract BibTeX arXiv:1810.13084

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Revisiting Randomized Gossip Algorithms: General Framework, Convergence Rates and Novel Block and Accelerated Protocols

2019-05-20 · Nicolas Loizou, Peter Richtárik

In this work we present a new framework for the analysis and design of randomized gossip algorithms for solving the average consensus problem. We show how classical randomized iterative methods for solving linear systems…

Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives

2018-10-05 · Hadrien Hendrikx, Francis Bach, Laurent Massoulié

In this paper, we study the problem of minimizing a sum of smooth and strongly convex functions split over the nodes of a network in a decentralized fashion. We propose the algorithm $ESDACD$, a decentralized accelerated…

Accelerated Gossip via Stochastic Heavy Ball Method

2018-09-23 · Nicolas Loizou, Peter Richtárik

In this paper we show how the stochastic heavy ball method (SHB) -- a popular method for solving stochastic convex and non-convex optimization problems --operates as a randomized gossip algorithm. In particular, we focus…

Accelerated Randomized Coordinate Descent Algorithms for Stochastic Optimization and Online Learning

2018-06-05 · Akshita Bhandari, Chandramani Singh

We propose accelerated randomized coordinate descent algorithms for stochastic optimization and online learning. Our algorithms have significantly less per-iteration complexity than the known accelerated gradient algorit…

Stochastic Optimization

A Privacy Preserving Randomized Gossip Algorithm via Controlled Noise Insertion

2019-01-27 · Filip Hanzely, Jakub Konečný, Nicolas Loizou, Peter Richtárik 외

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 stored at the nodes. We give iteration co…

Privacy Preserving