30 citations · 57 across the 2 of their papers we have counts for
2 papers
cs.LG2014★ 27 cited
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning
Francesco Orabona
Stochastic gradient descent algorithms for training linear and kernel predictors are gaining more and more importance, thanks to their scalability. While various methods have been…
math.OC2012★ 30 cited
PRISMA: PRoximal Iterative SMoothing Algorithm
Francesco Orabona, Andreas Argyriou, Nathan Srebro
Motivated by learning problems including max-norm regularized matrix completion and clustering, robust PCA and sparse inverse covariance selection, we propose a novel optimization…