10 citations · 24 across the 6 of their papers we have counts for
4 papers · 1 filter
Scalable Frank-Wolfe on Generalized Self-concordant Functions via Simple Steps
Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta
Generalized self-concordance is a key property present in the objective function of many important learning problems. We establish the convergence rate of a simple Frank-Wolfe vari…
FrankWolfe.jl: a high-performance and flexible toolbox for Frank-Wolfe algorithms and Conditional Gradients
Mathieu Besançon, Alejandro Carderera, Sebastian Pokutta
We present FrankWolfe.jl, an open-source implementation of several popular Frank-Wolfe and Conditional Gradients variants for first-order constrained optimization. The package is d…
Parameter-free Locally Accelerated Conditional Gradients
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin +1
Projection-free conditional gradient (CG) methods are the algorithms of choice for constrained optimization setups in which projections are often computationally prohibitive but li…
CINDy: Conditional gradient-based Identification of Non-linear Dynamics -- Noise-robust recovery
Alejandro Carderera, Sebastian Pokutta, Christof Schütte +1
Governing equations are essential to the study of nonlinear dynamics, often enabling the prediction of previously unseen behaviors as well as the inclusion into control strategies.…