Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Nicolas Loizou"'
Autor:
Nicolas Loizou, Peter Richtárik
Publikováno v:
IEEE Transactions on Information Theory. 67:8300-8324
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 can be interpreted as gossip
Publikováno v:
ICASSP
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
Autor:
Nicolas Loizou, Peter Richtárik
In this paper we present a convergence rate analysis of inexact variants of several randomized iterative methods. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic subspace ascent.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10ff1ebef33819b2d71354d4d7a67c91
Autor:
Peter Richtárik, Nicolas Loizou
Publikováno v:
Allerton
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 on two special cases of SHB:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c68300f023d5472304c2fa7fee680e5
http://arxiv.org/abs/1809.08657
http://arxiv.org/abs/1809.08657
Autor:
Nicolas Loizou, Peter Richtárik
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace asce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84f40babe59c4e2374ae62946068c01c
Autor:
Nicolas Loizou
Publikováno v:
ICORES
We present a new model of incomplete information games without private information in which the players use a distributionally robust optimization approach to cope with the payoff uncertainty. With some specific restrictions, we show that our "Distri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a19cdc6c2f4b8e925cba7d95855b4f62
Autor:
Peter Richtárik, Nicolas Loizou
Publikováno v:
Loizou, N & Richtárik, P 2017, ' A New Perspective on Randomized Gossip Algorithms ', Paper presented at 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, Washington, United States, 7/12/16-9/12/16 . < https://ieeexplore.ieee.org/document/7905880/ >
GlobalSIP
GlobalSIP
In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how that Randomized Block Kaczmarz (RBK) method - a method for solving linear s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a73e8f0016d3c6d2a7a3e53ef05fcde