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Most algorithms for solving optimization problems or finding saddle points of convex-concave functions are fixed-point algorithms.
Introductory lectures on convex optimization: a basic course
Nesterov, Y · 2004
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Fixed-Point Algorithms for Inverse Problems in Science and Engineering
Bauschke, H. H., Burachik, R. S., Combettes, P. L., Elser, V., Luke, D. R., and Wolkowicz, H. (eds.) · 2011
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On decomposing the proximal map
Yu, Y.-L · 2013
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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
Richtárik, P. and Takáč, M · 2014
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Compositions and convex combinations of averaged nonexpansive operators
Combettes, P. L. and Yamada, I · 2015
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A class of randomized primal-dual algorithms for distributed optimization
Pesquet, J.-C. and Repetti, A · 2015
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Convergence rate analysis of several splitting schemes
Davis, D. and Yin, W · 2016
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Federated learning: Strategies for improving communication efficiency
Konečný, J., McMahan, H. B., Yu, F. X., Richtárik, P., Suresh, A. T., and Bacon, D · 2016
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Analysis and design of optimization algorithms via integral quadratic constraints
Lessard, L., Recht, B., and Packards, A · 2016
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Convex Analysis and Monotone Operator Theory in Hilbert Spaces
Bauschke, H. H. and Combettes, P. L · 2017
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Distributed optimization with arbitrary local solvers
Ma, C., Konečný, J., Jaggi, M., Smith, V., Jordan, M. I., Richtárik, P., and Takáč, M · 2017
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Communication-efficient learning of deep networks from decentralized data
McMahan, H. B., Moore, E., Ramage, D., Hampson, S., and Agüera y Arcas, B · 2017
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On the convergence of local descent methods in federated learning
Haddadpour, F. and Mahdavi, M · 2019
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Gradient descent with compressed iterates
Khaled, A. and Richtárik, P · 2019
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First analysis of local GD on heterogeneous data
Khaled, A., Mishchenko, K., and Richtárik, P · 2019
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Local SGD Converges Fast and Communicates Little
Stich, S. U · 2019
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A fixed point framework for recovering signals from nonlinear transformations
Combettes, P. L. and Woodstock, Z. C · 2020
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Tighter theory for local SGD on identical and heterogeneous data
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Chraibi, S., Khaled, A., Kovalev, D., Richtárik, P., Salim, A., and Takáč, M · 2019
Cited alongside, same era.
Khaled, A., Mishchenko, K., and Richtárik, P · 2020
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