41 citations · 109 across the 18 of their papers we have counts for
3 papers · 1 filter
Dropout as a Low-Rank Regularizer for Matrix Factorization
Jacopo Cavazza, Pietro Morerio, Benjamin Haeffele +3
Regularization for matrix factorization (MF) and approximation problems has been carried out in many different ways. Due to its popularity in deep learning, dropout has been applie…
An Analysis of Dropout for Matrix Factorization
Jacopo Cavazza, Connor Lane, Benjamin D. Haeffele +2
Dropout is a simple yet effective algorithm for regularizing neural networks by randomly dropping out units through Bernoulli multiplicative noise, and for some restricted problem…
Active Regression with Adaptive Huber Loss
Jacopo Cavazza, Vittorio Murino
This paper addresses the scalar regression problem through a novel solution to exactly optimize the Huber loss in a general semi-supervised setting, which combines multi-view learn…