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- research-articleMarch 2024
Beyond spectral gap: the role of the topology in decentralized learning
The Journal of Machine Learning Research (JMLR), Volume 24, Issue 1Article No.: 355, Pages 17074–17104In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers ...
- research-articleJanuary 2018
Optimal Affine-Invariant Smooth Minimization Algorithms
SIAM Journal on Optimization (SIOPT), Volume 28, Issue 3Pages 2384–2405https://doi.org/10.1137/17M1116842We formulate an affine-invariant implementation of the accelerated first-order algorithm in [Y. Nesterov, Dokl. Math., 27 (1983), pp. 372--376]. Its complexity bound is proportional to an affine-invariant regularity constant defined with respect to the ...
- articleJanuary 2017
CoCoA: a general framework for communication-efficient distributed optimization
The scale of modern datasets necessitates the development of efficient distributed optimization methods for machine learning. We present a general-purpose framework for distributed computing environments, CoCoA, that has an efficient communication ...
- research-articleDecember 2012
Approximating parameterized convex optimization problems
ACM Transactions on Algorithms (TALG), Volume 9, Issue 1Article No.: 10, Pages 1–17https://doi.org/10.1145/2390176.2390186We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an ϵ-approximate solution (and a corresponding ϵ-coreset) along the entire parameter ...