Search Results - "Conditional Gradient Algorithm"

A stochastic conditional gradient algorithm for decentralized online convex optimization by Thắng, Nguyễn Kim, Srivastav, Abhinav, Trystram, Denis, Youssef, Paul

“…We study in this paper several problems at the intersection of decentralized optimization and online learning. Decentralized optimization plays a vital role in…”
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Constrained tensorial total variation problem based on an alternating conditional gradient algorithm by Benchettou, Oumaima, Bentbib, Abdeslem Hafid, Bouhamidi, Abderrahman, Kreit, Karim

“…The present paper aims to regularize ill-posed high-dimensional problems using a constrained total variation minimization approach. The analysis of the…”
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TADCG: A Novel Gridless Tomographic SAR Imaging Approach based on the Alternate Descent Conditional Gradient Algorithm with Robustness and Efficiency by Shao, Mingxiao, Zhang, Zhe, Li, Jie, Kang, Jian, Zhang, Bingchen

“…Sparse signal processing techniques, such as compressed sensing, are commonly employed in tomographic synthetic aperture radar (TomoSAR) imaging due to the…”
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A conditional gradient algorithm for distributed online optimization in networks by Shen, Xiuyu, Li, Dequan, Fang, Runyue, Dong, Qiao

“… any central coordinator. An online distributed conditional gradient algorithm based on the conditional gradient is developed, which can effectively tackle the problem of high time complexity of the distributed online optimisation…”
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An efficient first-order conditional gradient algorithm in data-driven sparse identification of nonlinear dynamics to solve sparse recovery problems under noise by Carderera, Alejandro, Pokutta, Sebastian, Schütte, Christof, Weiser, Martin

“… We propose an efficient first-order Conditional Gradient algorithm for solving the underlying optimization problem…”
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A Novel Gridless Non-Uniform Linear Array Direction of Arrival Estimation Approach Based on the Improved Alternating Descent Conditional Gradient Algorithm for Automotive Radar System by Shao, Mingxiao, Fan, Yizhe, Zhang, Yan, Zhang, Zhe, Zhao, Jie, Zhang, Bingchen

“…In automotive millimeter-wave (MMW) radar systems, achieving high-precision direction of arrival (DOA) estimation with a limited number of array elements is a…”
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Splitting the Conditional Gradient Algorithm by Woodstock, Zev, Pokutta, Sebastian

“…We propose a novel generalization of the conditional gradient (CG / Frank-Wolfe) algorithm for minimizing a smooth function \(f\) under an intersection of…”
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A Nonsmooth Frank–Wolfe Algorithm Through a Dual Cutting-Plane Approach by Mazanti, Guilherme, Moquet, Thibault, Pfeiffer, Laurent

“…An extension of the Frank–Wolfe Algorithm (FWA), also known as Conditional Gradient algorithm, is proposed…”
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Distributed Conditional Gradient Algorithm for Two-Network Saddle-point Problem by Hou, Jie, Zeng, Xianlin

“…We consider a two-network saddle-point problem with constraints, whose projections are expensive. We propose a projection-free algorithm, which is referred to…”
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Primal and dual predicted decrease approximation methods by Beck, Amir, Pauwels, Edouard, Sabach, Shoham

“…We introduce the notion of predicted decrease approximation (PDA) for constrained convex optimization, a flexible framework which includes as special cases…”
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Linear-memory and Decomposition-invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes by Garber, Dan, Meshi, Ofer

“…Recently, several works have shown that natural modifications of the classical conditional gradient method (aka Frank-Wolfe algorithm) for constrained convex…”
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A Linearly Convergent Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization by Garber, Dan, Hazan, Elad

“… Our main result is a novel conditional gradient algorithm for smooth and strongly convex optimization over polyhedral sets that performs only a single linear optimization step over the domain…”
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Convergence of a conditional gradient algorithm for relaxed controls involving first boundary value problems of parabolic type by Teo, K. L.

“…In this paper, we consider a class of optimal control problems involving linear first boundary value problems of parabolic type. A conditional gradient method…”
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Conditional gradient algorithms for norm-regularized smooth convex optimization by Harchaoui, Zaid, Juditsky, Anatoli, Nemirovski, Arkadi

“…Motivated by some applications in signal processing and machine learning, we consider two convex optimization problems where, given a cone K , a norm ‖ · ‖ and…”
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Conditional Gradient Algorithms for Rank-One Matrix Approximations with a Sparsity Constraint by Luss, Ronny, Teboulle, Marc

“… Building on the old and well-known conditional gradient algorithm, ConGradU is a simplified version with unit step size that yields a generic algorithm which either is given by an analytic formula…”
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Faster Conditional Gradient Algorithms for Machine Learning by de Diego, Alejandro Agustín Carderera

“…In this thesis, we focus on Frank-Wolfe (a.k.a. Conditional Gradient) algorithms,a family of iterative algorithms for convex optimization, that work…”
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Partial alignment of multislice spatially resolved transcriptomics data by Liu, Xinhao, Zeira, Ron, Raphael, Benjamin J

“…Spatially resolved transcriptomics (SRT) technologies measure messenger RNA (mRNA) expression at thousands of locations in a tissue slice. However, nearly all…”
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Decentralized Frank-Wolfe Algorithm for Convex and Nonconvex Problems by Hoi-To Wai, Lafond, Jean, Scaglione, Anna, Moulines, Eric

“… To address this problem, this paper adopts a projection-free optimization approach, a.k.a. the Frank-Wolfe (FW) or conditional gradient algorithm…”
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Lazifying Conditional Gradient Algorithms by Braun, Gábor, Pokutta, Sebastian, Zink, Daniel

“…Conditional gradient algorithms (also often called Frank-Wolfe algorithms) are popular due to their simplicity of only requiring a linear optimization oracle and more recently they also gained significant traction for online learning…”
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Maximum likelihood estimation for totally positive log‐concave densities by Robeva, Elina, Sturmfels, Bernd, Tran, Ngoc, Uhler, Caroline

“…We study nonparametric maximum likelihood estimation for two classes of multivariate distributions that imply strong forms of positive dependence; namely…”
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