Výsledky vyhľadávania - block‐coordinate gradient descent algorithm

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    A novel blockcoordinate gradient descent algorithm for simultaneous grouped selection of fixed and random effects in joint modeling Autor Chen, Shuyan, Fang, Zhiqing, Li, Zhong, Liu, Xin

    ISSN: 0277-6715, 1097-0258, 1097-0258
    Vydavateľské údaje: Hoboken, USA John Wiley & Sons, Inc 15.10.2024
    Vydané v Statistics in medicine (15.10.2024)
    “… In this article, we propose a novel blockcoordinate gradient descent (BCGD) algorithm to simultaneously select multiple longitudinal covariates that may carry…”
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    Convergence of gradient-based block coordinate descent algorithms for non-orthogonal joint approximate diagonalization of matrices Autor Li, Jianze, Usevich, Konstantin, Comon, Pierre

    ISSN: 0895-4798, 1095-7162
    Vydavateľské údaje: Society for Industrial and Applied Mathematics 27.04.2023
    “…In this paper, we propose a gradient based block coordinate descent (BCD-G) framework to solve the joint approximate diagonalization of matrices defined on the product of the complex Stiefel manifold and the special linear group…”
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    A Block Coordinate Descent-Based Projected Gradient Algorithm for Orthogonal Non-Negative Matrix Factorization Autor Asadi, Soodabeh, Povh, Janez

    ISSN: 2227-7390, 2227-7390
    Vydavateľské údaje: MDPI AG 01.03.2021
    Vydané v Mathematics (Basel) (01.03.2021)
    “…), where one or both matrix factors must have orthonormal columns or rows. We penalize the orthonormality constraints and apply the PG method via a block coordinate descent approach…”
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    Iteration complexity analysis of block coordinate descent methods Autor Hong, Mingyi, Wang, Xiangfeng, Razaviyayn, Meisam, Luo, Zhi-Quan

    ISSN: 0025-5610, 1436-4646
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2017
    Vydané v Mathematical programming (01.05.2017)
    “…In this paper, we provide a unified iteration complexity analysis for a family of general block coordinate descent methods, covering popular methods such as the block coordinate gradient descent…”
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    An Improved Adam Optimization Algorithm Combining Adaptive Coefficients and Composite Gradients Based on Randomized Block Coordinate Descent Autor Liu, Miaomiao, Yao, Dan, Liu, Zhigang, Guo, Jingfeng, Chen, Jing

    ISSN: 1687-5265, 1687-5273, 1687-5273
    Vydavateľské údaje: United States Hindawi 2023
    “…An improved Adam optimization algorithm combining adaptive coefficients and composite gradients based on randomized block coordinate descent is proposed to address issues of the Adam algorithm…”
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    Structured feature selection using coordinate descent optimization Autor Ghalwash, Mohamed F., Cao, Xi Hang, Stojkovic, Ivan, Obradovic, Zoran

    ISSN: 1471-2105, 1471-2105
    Vydavateľské údaje: London BioMed Central 08.04.2016
    Vydané v BMC bioinformatics (08.04.2016)
    “… optimization problems so that the problem can be solved by any standard optimization algorithm…”
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    Convergence of gradient-based block coordinate descent algorithms for non-orthogonal joint approximate diagonalization of matrices Autor Li, Jianze, Usevich, Konstantin, Comon, Pierre

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 25.04.2023
    Vydané v arXiv.org (25.04.2023)
    “…In this paper, we propose a gradient-based block coordinate descent (BCD-G) framework to solve the joint approximate diagonalization of matrices defined on the product of the complex Stiefel manifold and the special linear group…”
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    A Local Block Coordinate Descent Algorithm for the CSC Model Autor Zisselman, Ev, Sulam, Jeremias, Elad, Michael

    ISSN: 1063-6919
    Vydavateľské údaje: IEEE 01.06.2019
    “… In this work we propose a new and simple approach that adopts a localized strategy, based on the Block Coordinate Descent algorithm…”
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    A Block Coordinate Descent-based Projected Gradient Algorithm for Orthogonal Non-negative Matrix Factorization Autor Asadi, Soodabeh, Povh, Janez

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 23.03.2020
    Vydané v arXiv.org (23.03.2020)
    “…), where one or both matrix factors must have orthonormal columns or rows. We penalise the orthonormality constraints and apply the PG method via a block coordinate descent approach…”
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    Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator Autor Yuning Yang, Yunlong Feng, Suykens, Johan A. K.

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydavateľské údaje: United States IEEE 01.09.2016
    “…This paper addresses the robust low-rank tensor recovery problems. Tensor recovery aims at reconstructing a low-rank tensor from some linear measurements,…”
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    Low-rank matrix factorization with nonconvex regularization and bilinear decomposition Autor Wang, Sijie, Xia, Kewen, Wang, Li, Yin, Zhixian, He, Ziping, Zhang, Jiangnan, Aslam, Naila

    ISSN: 0165-1684
    Vydavateľské údaje: Elsevier B.V 01.12.2022
    Vydané v Signal processing (01.12.2022)
    “…•A non-convex bilinear low-rank matrix factorization model is proposed.•A block coordinate descent based algorithm is derived with convergence conditions…”
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    Online Learning for DNN Training: A Stochastic Block Adaptive Gradient Algorithm Autor Liu, Jianghui, Li, Baozhu, Zhou, Yangfan, Zhao, Xuhui, Zhu, Junlong, Zhang, Mingchuan

    ISSN: 1687-5265, 1687-5273, 1687-5273
    Vydavateľské údaje: United States Hindawi 2022
    “… In this algorithm, stochastic block coordinate descent and the adaptive learning rate are utilized at each iteration…”
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    Direct Optimization of the Dictionary Learning Problem Autor Rakotomamonjy, Alain

    ISSN: 1053-587X, 1941-0476
    Vydavateľské údaje: New York, NY IEEE 01.11.2013
    “… The algorithm we advocate simply performs a joint proximal gradient descent step over the dictionary atoms and the coefficient matrix…”
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    FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features Autor Liu, Yang, Zhang, Xinwei, Kang, Yan, Li, Liping, Chen, Tianjian, Hong, Mingyi, Yang, Qiang

    ISSN: 1053-587X, 1941-0476
    Vydavateľské údaje: New York IEEE 2022
    “… over sharing such messages during learning. We propose a Federated Stochastic Block Coordinate Descent (FedBCD…”
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    Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators Autor Li, Xiuxian, Xie, Lihua

    ISSN: 0005-1098, 1873-2836
    Vydavateľské údaje: Elsevier Ltd 01.12.2020
    Vydané v Automatica (Oxford) (01.12.2020)
    “… To solve the problem, two algorithms are developed, called distributed Krasnosel’skiĭ–Mann (D-KM) and distributed block-coordinate…”
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    Asynchronous incremental block-coordinate descent Autor Aytekin, Arda, Feyzmahdavian, Hamid Reza, Johansson, Mikael

    Vydavateľské údaje: IEEE 01.09.2014
    “… In our algorithm, a coordinator updates a global iterate based on delayed partial gradients of the individual objective functions with respect to blocks of coordinates…”
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    Stochastic Augmented Projected Gradient Methods for the Large-Scale Precoding Matrix Indicator Selection Problem Autor Zhang, Jiaqi, Jin, Zeyu, Jiang, Bo, Wen, Zaiwen

    ISSN: 1536-1276, 1558-2248
    Vydavateľské údaje: New York IEEE 01.11.2022
    “… The discrete constraints in the formulations make the problem NP-hard. Then we propose a stochastic projected gradient method augmented by block coordinate descent under various strategies…”
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    Inexact Block Coordinate Descent Algorithms for Nonsmooth Nonconvex Optimization Autor Yang, Yang, Pesavento, Marius, Luo, Zhi-Quan, Ottersten, Bjorn

    ISSN: 1053-587X, 1941-0476
    Vydavateľské údaje: New York IEEE 2020
    “…In this paper, we propose an inexact block coordinate descent algorithm for large-scale nonsmooth nonconvex optimization problems…”
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    A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion Autor Xu, Yangyang, Yin, Wotao

    ISSN: 1936-4954, 1936-4954
    Vydavateľské údaje: Philadelphia Society for Industrial and Applied Mathematics 01.01.2013
    Vydané v SIAM journal on imaging sciences (01.01.2013)
    “… We review some interesting applications and propose a generalized block coordinate descent method…”
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