355 citations · 1.6k across the 54 of their papers we have counts for
5 papers · 1 filter
Iterative regularization in classification via hinge loss diagonal descent
Vassilis Apidopoulos, Tomaso Poggio, Lorenzo Rosasco +1
Iterative regularization is a classic idea in regularization theory, that has recently become popular in machine learning. On the one hand, it allows to design efficient algorithms…
For interpolating kernel machines, minimizing the norm of the ERM solution minimizes stability
Akshay Rangamani, Lorenzo Rosasco, Tomaso Poggio
We study the average $\mbox{CV}_{loo}$ stability of kernel ridge-less regression and derive corresponding risk bounds. We show that the interpolating solution with minimum norm min…
Approximate inference with Wasserstein gradient flows
Charlie Frogner, Tomaso Poggio
We present a novel approximate inference method for diffusion processes, based on the Wasserstein gradient flow formulation of the diffusion. In this formulation, the time-dependen…
On Learnability, Complexity and Stability
Silvia Villa, Lorenzo Rosasco, Tomaso Poggio
We consider the fundamental question of learnability of a hypotheses class in the supervised learning setting and in the general learning setting introduced by Vladimir Vapnik. We…
Multiclass Learning with Simplex Coding
Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco +1
In this paper we discuss a novel framework for multiclass learning, defined by a suitable coding/decoding strategy, namely the simplex coding, that allows to generalize to multiple…