37 citations · 56 across the 4 of their papers we have counts for
4 papers
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…
Convex Learning of Multiple Tasks and their Structure
Carlo Ciliberto, Youssef Mroueh, Tomaso Poggio +1
Reducing the amount of human supervision is a key problem in machine learning and a natural approach is that of exploiting the relations (structure) among different tasks. This is…
Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn?
Giulia Pasquale, Carlo Ciliberto, Francesca Odone +2
The ability to visually recognize objects is a fundamental skill for robotics systems. Indeed, a large variety of tasks involving manipulation, navigation or interaction with other…
Learning Multiple Visual Tasks while Discovering their Structure
Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa
Multi-task learning is a natural approach for computer vision applications that require the simultaneous solution of several distinct but related problems, e.g. object detection, c…