639 citations · 2.9k across the 94 of their papers we have counts for
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A Bridge Between Hyperparameter Optimization and Learning-to-learn
Luca Franceschi, Michele Donini, Paolo Frasconi +1
We consider a class of a nested optimization problems involving inner and outer objectives. We observe that by taking into explicit account the optimization dynamics for the inner…
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…
Quantum machine learning: a classical perspective
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo +4
Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classifica…
Consistent Multitask Learning with Nonlinear Output Relations
Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco +1
Key to multitask learning is exploiting relationships between different tasks to improve prediction performance. If the relations are linear, regularization approaches can be used…
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi, Michele Donini, Paolo Frasconi +1
We study two procedures (reverse-mode and forward-mode) for computing the gradient of the validation error with respect to the hyperparameters of any iterative learning algorithm s…