43 citations · 280 across the 42 of their papers we have counts for
4 papers · 2 filters
Proximal methods avoid active strict saddles of weakly convex functions
Damek Davis, Dmitriy Drusvyatskiy
We introduce a geometrically transparent strict saddle property for nonsmooth functions. This property guarantees that simple proximal algorithms on weakly convex problems converge…
Stochastic algorithms with geometric step decay converge linearly on sharp functions
Damek Davis, Dmitriy Drusvyatskiy, Vasileios Charisopoulos
Stochastic (sub)gradient methods require step size schedule tuning to perform well in practice. Classical tuning strategies decay the step size polynomially and lead to optimal sub…
From low probability to high confidence in stochastic convex optimization
Damek Davis, Dmitriy Drusvyatskiy, Lin Xiao +1
Standard results in stochastic convex optimization bound the number of samples that an algorithm needs to generate a point with small function value in expectation. More nuanced hi…
Composite optimization for robust blind deconvolution
Vasileios Charisopoulos, Damek Davis, Mateo Díaz +1
The blind deconvolution problem seeks to recover a pair of vectors from a set of rank one bilinear measurements. We consider a natural nonsmooth formulation of the problem and show…