5 citations · 19 across the 8 of their papers we have counts for
4 papers · 1 filter
Heavy Ball Momentum for Conditional Gradient
Bingcong Li, Alireza Sadeghi, Georgios B. Giannakis
Conditional gradient, aka Frank Wolfe (FW) algorithms, have well-documented merits in machine learning and signal processing applications. Unlike projection-based methods, momentum…
Enhancing Parameter-Free Frank Wolfe with an Extra Subproblem
Bingcong Li, Lingda Wang, Georgios B. Giannakis +1
Aiming at convex optimization under structural constraints, this work introduces and analyzes a variant of the Frank Wolfe (FW) algorithm termed ExtraFW. The distinct feature of Ex…
How Does Momentum Help Frank Wolfe?
Bingcong Li, Mario Coutino, Georgios B. Giannakis +1
We unveil the connections between Frank Wolfe (FW) type algorithms and the momentum in Accelerated Gradient Methods (AGM). On the negative side, these connections illustrate why mo…
Tight Linear Convergence Rate of ADMM for Decentralized Optimization
Meng Ma, Bingcong Li, Georgios B. Giannakis
The present paper considers leveraging network topology information to improve the convergence rate of ADMM for decentralized optimization, where networked nodes work collaborative…