97 citations · 184 across the 26 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…
Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications
Benjamin D. Haeffele, Rene Vidal
Recently, convex formulations of low-rank matrix factorization problems have received considerable attention in machine learning. However, such formulations often require solving f…