iPiano: Inertial Proximal Algorithm for Non-Convex Optimization

18 April 2014

Thomas Brox

Papers citing "iPiano: Inertial Proximal Algorithm for Non-Convex Optimization"

50 / 72 papers shown

Title
A Generalization Result for Convergence in Learning-to-Optimize Michael Sucker Peter Ochs 89 0 0 10 Oct 2024
Deep Inertia $L_p$ Half-Quadratic Splitting Unrolling Network for Sparse View CT Reconstruction Yu Guo Caiying Wu Yaxin Li Qiyu Jin Tieyong Zeng 47 0 0 13 Aug 2024
Block Majorization Minimization with Extrapolation and Application to $β$ -NMF L. Hien Valentin Leplat Nicolas Gillis 80 3 0 12 Jan 2024
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization Junwen Qiu Xiao Li Andre Milzarek 104 3 0 02 Dec 2023
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter Samuel Hurault A. Chambolle Arthur Leclaire Nicolas Papadakis 51 6 0 02 Nov 2023
Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms Alexis Goujon Sebastian Neumayer M. Unser 94 24 0 21 Aug 2023
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems Samuel Hurault Ulugbek Kamilov Arthur Leclaire Nicolas Papadakis 75 11 0 06 Jun 2023
Optimization-Inspired Cross-Attention Transformer for Compressive Sensing Jie Song Chong Mou Shiqi Wang Siwei Ma Jian Zhang 93 38 0 27 Apr 2023
Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting Karl Schrader Pascal Peter Niklas Kämper Joachim Weickert 45 3 0 17 Mar 2023
A relaxed proximal gradient descent algorithm for convergent plug-and-play with proximal denoiser Samuel Hurault A. Chambolle Arthur Leclaire Nicolas Papadakis 59 12 0 31 Jan 2023
DRSOM: A Dimension Reduced Second-Order Method Chuwen Zhang Dongdong Ge Chang He Bo Jiang Yuntian Jiang Yi-Li Ye 55 5 0 30 Jul 2022
Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization Samuel Hurault Arthur Leclaire Nicolas Papadakis 140 77 0 31 Jan 2022
$Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^{-7/4})$ Complexity$ Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^{-7/4})$ Complexity Huan Li Zhouchen Lin 112 24 0 27 Jan 2022
Accelerated Gradient Flow: Risk, Stability, and Implicit Regularization Yue Sheng Alnur Ali 108 2 0 20 Jan 2022
Accelerated Proximal Alternating Gradient-Descent-Ascent for Nonconvex Minimax Machine Learning Ziyi Chen Shaocong Ma Yi Zhou 58 8 0 22 Dec 2021
Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization Tao Sun Huaming Ling Zuoqiang Shi Dongsheng Li Bao Wang ODL 65 13 0 18 Oct 2021
A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization C. Alecsa 55 0 0 16 Oct 2021
Convergence of Random Reshuffling Under The Kurdyka-Łojasiewicz Inequality Xiao Li Andre Milzarek Junwen Qiu 95 20 0 10 Oct 2021
Gradient Step Denoiser for convergent Plug-and-Play Samuel Hurault Arthur Leclaire Nicolas Papadakis 70 97 0 07 Oct 2021
Learning Sparse Masks for Diffusion-based Image Inpainting Tobias Alt Pascal Peter Joachim Weickert DiffM 60 13 0 06 Oct 2021
Distributed stochastic inertial-accelerated methods with delayed derivatives for nonconvex problems Yangyang Xu Yibo Xu Yonggui Yan Jiewei Chen 66 4 0 24 Jul 2021
Escaping Saddle Points Faster with Stochastic Momentum Jun-Kun Wang Chi-Heng Lin Jacob D. Abernethy ODL 77 22 0 05 Jun 2021
A Refined Inertial DC Algorithm for DC Programming Yu You Yi-Shuai Niu 26 7 0 30 Apr 2021
The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods Wei Tao Sheng Long Gao-wei Wu Qing Tao 38 14 0 15 Feb 2021
Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training Linbo Qiao Tao Sun H. Pan Dongsheng Li 51 3 0 30 Jan 2021
Mixed-type multivariate response regression with covariance estimation Karl Oskar Ekvall Aaron J. Molstad 13 6 0 21 Jan 2021
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms Mahesh Chandra Mukkamala M. Fadili Peter Ochs 71 8 0 24 Dec 2020
AEGD: Adaptive Gradient Descent with Energy Hailiang Liu Xuping Tian ODL 55 11 0 10 Oct 2020
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction Yunmei Chen Hongcheng Liu X. Ye Qingchao Zhang 161 23 0 22 Jul 2020
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning Zhenzhang Ye Thomas Möllenhoff Tao Wu Daniel Cremers 18 3 0 27 Feb 2020
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization Yi Zhou Zhe Wang Kaiyi Ji Yingbin Liang Vahid Tarokh 47 8 0 26 Feb 2020
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization Vien V. Mai M. Johansson 89 56 0 13 Feb 2020
Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Non Convex Optimization Anas Barakat Pascal Bianchi 77 12 0 18 Nov 2019
Bregman Proximal Framework for Deep Linear Neural Networks Mahesh Chandra Mukkamala Felix Westerkamp Emanuel Laude Daniel Cremers Peter Ochs 77 7 0 08 Oct 2019
Variational Osmosis for Non-linear Image Fusion S. Parisotto L. Calatroni Aurélie Bugeau Nicolas Papadakis Carola-Bibiane Schönlieb 16 24 0 04 Oct 2019
Randomized Iterative Methods for Linear Systems: Momentum, Inexactness and Gossip Nicolas Loizou 65 5 0 26 Sep 2019
Inertial nonconvex alternating minimizations for the image deblurring Tao Sun R. Barrio Marcos Rodríguez Hao Jiang 47 12 0 27 Jul 2019
Heavy-ball Algorithms Always Escape Saddle Points Tao Sun Dongsheng Li Zhe Quan Hao Jiang Shengguo Li Y. Dou ODL 56 21 0 23 Jul 2019
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms Mahesh Chandra Mukkamala Peter Ochs 78 23 0 22 May 2019
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization Mahesh Chandra Mukkamala Peter Ochs Thomas Pock Shoham Sabach 55 52 0 06 Apr 2019
Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization L. Hien Nicolas Gillis Panagiotis Patrinos 34 11 0 05 Mar 2019
Time-Delay Momentum: A Regularization Perspective on the Convergence and Generalization of Stochastic Momentum for Deep Learning Ziming Zhang Wenju Xu Alan Sullivan 99 1 0 02 Mar 2019
Non-ergodic Convergence Analysis of Heavy-Ball Algorithms Tao Sun Penghang Yin Dongsheng Li Chun Huang Lei Guan Hao Jiang 58 46 0 05 Nov 2018
On the Generalization of Stochastic Gradient Descent with Momentum Ali Ramezani-Kebrya Kimon Antonakopoulos Volkan Cevher Ashish Khisti Ben Liang MLT 73 26 0 12 Sep 2018
A Unified Analysis of Stochastic Momentum Methods for Deep Learning Yan Yan Tianbao Yang Zhe Li Qihang Lin Yi Yang 53 120 0 30 Aug 2018
Proximal boosting: aggregating weak learners to minimize non-differentiable losses Erwan Fouillen C. Boyer Maxime Sangnier FedML 70 2 0 29 Aug 2018
Composite Optimization by Nonconvex Majorization-Minimization Jonas Geiping Michael Möller 49 17 0 20 Feb 2018
Non-ergodic Complexity of Convex Proximal Inertial Gradient Descents Tao Sun Linbo Qiao Penghang Yin 30 0 0 23 Jan 2018
On the Proximal Gradient Algorithm with Alternated Inertia F. Iutzeler J. Malick 44 33 0 17 Jan 2018
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods Nicolas Loizou Peter Richtárik 80 204 0 27 Dec 2017