Dec 5, 2016 · This paper adopts a projection-free optimization approach, aka~the Frank-Wolfe (FW) or conditional gradient algorithm.
From the algorithmic perspective, the FW algorithm replaces the costly projection step in PG based algorithms with a constrained linear optimization, which ...
To address this problem, this paper adopts a projection-free optimization approach, a.k.a. the Frank-Wolfe (FW) or conditional gradient algorithm. We first ...
The advantages of the proposed DeFW algorithm on low-complexity robust matrix completion and communication efficient sparse learning are demonstrated, ...
Oct 25, 2017 · Abstract—Decentralized optimization algorithms have re- ceived much attention due to the recent advances in network information processing.
Oct 22, 2024 · ... The FW algorithm uses a linear approximation of the objective function and solves a linear programming problem. In this paper the ...
In this paper, we answer the above challenging question with positive solution and propose a novel Decentralized. Quantized Stochastic Frank-Wolfe (DQSFW) ...
IEEE Transactions on Automatic Control, 62(11):5522–5537, IEEE, 2017. Decentralized Frank–Wolfe algorithm for convex and nonconvex problems [link] Code ...
Companion codes for the paper "Decentralized Frank-Wolfe Algorithm for Convex and Non-convex Problems", accepted by IEEE TAC, to appear, 2017.
People also ask
Can stochastic zeroth order Frank Wolfe method converge faster for non convex problems?
What is the Frank Wolfe algorithm?
Decentralized Frank–Wolfe algorithm for convex and nonconvex problems. HT Wai, J Lafond, A Scaglione, E Moulines. IEEE Transactions on Automatic Control 62 (11) ...