4 citations · 7 across the 3 of their papers we have counts for
3 papers · 1 filter
Online Parameter-Free Learning of Multiple Low Variance Tasks
Giulia Denevi, Dimitris Stamos, Massimiliano Pontil
We propose a method to learn a common bias vector for a growing sequence of low-variance tasks. Unlike state-of-the-art approaches, our method does not require tuning any hyper-par…
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
Giulia Luise, Dimitris Stamos, Massimiliano Pontil +1
We study the interplay between surrogate methods for structured prediction and techniques from multitask learning designed to leverage relationships between surrogate outputs. We p…
Reexamining Low Rank Matrix Factorization for Trace Norm Regularization
Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil
Trace norm regularization is a widely used approach for learning low rank matrices. A standard optimization strategy is based on formulating the problem as one of low rank matrix f…