Search Results - Alternating randomized proximal gradient algorithm

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  1. 1

    Zeroth-order single-loop algorithms for nonconvex-linear minimax problems by Shen, Jingjing, Wang, Ziqi, Xu, Zi

    ISSN: 0925-5001, 1573-2916
    Published: New York Springer US 01.11.2023
    Published in Journal of global optimization (01.11.2023)
    “… . Furthermore, we propose a zeroth-order alternating randomized proximal gradient algorithm for block-wise nonsmooth nonconvex-linear minimax problems and its corresponding iteration complexity is O K 3 2 ε…”
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    Journal Article
  2. 2

    Variational Analysis Perspective on Linear Convergence of Some First Order Methods for Nonsmooth Convex Optimization Problems by Ye, Jane J., Yuan, Xiaoming, Zeng, Shangzhi, Zhang, Jin

    ISSN: 1877-0533, 1877-0541
    Published: Dordrecht Springer Netherlands 01.12.2021
    Published in Set-valued and variational analysis (01.12.2021)
    “…), the proximal alternating linearized minimization (PALM) algorithm and the randomized block coordinate proximal gradient method (R-BCPGM…”
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    Journal Article
  3. 3

    Smoothing randomized block-coordinate proximal gradient algorithms for nonsmooth nonconvex composite optimization by Li, Xue, Bian, Wei

    ISSN: 1017-1398, 1572-9265
    Published: New York Springer US 01.09.2025
    Published in Numerical algorithms (01.09.2025)
    “…) algorithm and a Bregman randomized block-coordinate proximal gradient (B-RBCPG) algorithm for minimizing the sum of two nonconvex nonsmooth functions, one of which is block separable…”
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    Journal Article
  4. 4

    A Distributed Proximal Alternating Direction Multiplier Method for Multiblock Nonsmooth Composite Optimization by Zhou, Yuan, Guo, Luyao, Shi, Xinli, Cao, Jinde

    ISSN: 2325-5870, 2372-2533
    Published: Piscataway IEEE 01.03.2025
    “… To tackle this problem, we propose a novel distributed proximal alternating direction multiplier method (ADMM…”
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    Journal Article
  5. 5

    Derivative-free Alternating Projection Algorithms for General Nonconvex-Concave Minimax Problems by Xu, Zi, Wang, Ziqi, Shen, Jingjing, Dai, Yuhong

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 25.01.2024
    Published in arXiv.org (25.01.2024)
    “… Moreover, we propose a zeroth-order block alternating randomized proximal gradient algorithm (ZO-BAPG…”
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    Paper
  6. 6

    Inertial accelerated stochastic mirror descent for large-scale generalized tensor CP decomposition by Liu, Zehui, Wang, Qingsong, Cui, Chunfeng, Xia, Yong

    ISSN: 0926-6003, 1573-2894
    Published: New York Springer Nature B.V 01.05.2025
    “… This paper explores generalized tensor CP decomposition, employing the Bregman distance as the proximal term and introducing an inertial accelerated block randomized stochastic mirror descent algorithm (iTableSMD…”
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    Journal Article
  7. 7

    Random block-coordinate methods for inconsistent convex optimisation problems by Staudigl, Mathias, Jacquot, Paulin

    ISSN: 2730-5422, 2730-5422
    Published: Cham Springer International Publishing 06.11.2023
    “… Lying midway between the celebrated Chambolle–Pock primal-dual algorithm and Tseng’s accelerated proximal gradient method, we establish global convergence of the last iterate as well as optimal O ( 1 / k ) and O ( 1 / k 2…”
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    Journal Article
  8. 8

    Low-order Optimization Algorithms: Iteration Complexity and Applications by Gao, Xiang

    ISBN: 0438168461, 9780438168466
    Published: ProQuest Dissertations & Theses 01.01.2018
    “…Efficiency and scalability have become the new norms to evaluate optimization algorithms in the modern era of big data analytics…”
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    Dissertation
  9. 9

    Adaptive Catalyst for Smooth Convex Optimization by Ivanova, Anastasiya, Pasechnyuk, Dmitry, Grishchenko, Dmitry, Shulgin, Egor, Gasnikov, Alexander, Matyukhin, Vladislav

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 07.03.2021
    Published in arXiv.org (07.03.2021)
    “…In this paper, we present a generic framework that allows accelerating almost arbitrary non-accelerated deterministic and randomized algorithms for smooth convex optimization problems…”
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    Paper
  10. 10

    Efficiency of Coordinate Descent Methods For Structured Nonconvex Optimization by Deng, Qi, Lan, Chenghao

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 03.09.2019
    Published in arXiv.org (03.09.2019)
    “… First, by extending randomized CD to nonsmooth nonconvex settings, we develop a coordinate subgradient method that randomly updates block-coordinate variables by using block composite subgradient mapping…”
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    Paper