A fast distributed proximal-gradient method Autor Chen, Annie I., Ozdaglar, Asuman E.

“…We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private local objective of an agent in a network with time-varying topology. …”
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Composite optimization with coupling constraints via penalized proximal gradient method in asynchronous networks Autor Wang, Jianzheng, Hu, Guoqiang

“…To solve this problem, we propose an asynchronous penalized proximal gradient (Asyn-PPG) algorithm, a variant of classical proximal gradient method, with the presence of the asynchronous updates of the agents and uniform communication delays in the network. …”
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Composite optimization with coupling constraints via dual proximal gradient method with applications to asynchronous networks Autor Wang, Jianzheng, Hu, Guoqiang

“…In this article, we consider solving a composite optimization problem with affine coupling constraints in a multi-agent network based on proximal gradient method. In this problem, all the agents jointly minimize the sum of individual cost functions composed of smooth and possibly non-smooth parts. …”
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A Novel Approach for Solving Convex Problems with Cardinality Constraints Autor Banjac, G, Goulart, P

“…We propose a novel generalization of this problem and demonstrate that it is equivalent to the original sparsity-constrained problem if a certain weighting term is sufficiently large. We use the proximal gradient method to solve our generalized problem, and show that under certain regularity assumptions on the objective function the algorithm converges to a local minimum. …”

An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization Autor Yang, Heng, Liang, Ling, Carlone, Luca, Toh, Kim-Chuan

“…To solve the iPGM subproblem of projecting a given point onto the feasible set of the SDP, we design a two-phase algorithm with phase one using a symmetric Gauss–Seidel based accelerated proximal gradient method (sGS-APG) to generate a good initial point, and phase two using a modified limited-memory BFGS (L-BFGS) method to obtain an accurate solution. …”
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Enhanced extreme learning machine for general regression and classification tasks Autor Mahmood, Saif F

“…The proposed FASTA-ELM replaces the analytical step usually solved by SVD with an approximate solution through proximal gradient method, which dramatically speeds up the training time and improves the generalization ability in classification task. …”
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Proximal variable metric method with spectral diagonal update for large scale sparse optimization Autor Woo, Gillian Yi Han, Sim, Hong Seng, Goh, Yong Kheng, Leong, Wah June

“…The efficiency of the proposed method is compared against existing versions of proximal gradient methods on simulated datasets and large real-world MNIST datasets using Python software. …”

Fast distributed first-order methods Autor Chen, Annie I-An

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