105 citations · 199 across the 9 of their papers we have counts for
4 papers · 1 filter
Learning and Interpreting Multi-Multi-Instance Learning Networks
Alessandro Tibo, Manfred Jaeger, Paolo Frasconi
We introduce an extension of the multi-instance learning problem where examples are organized as nested bags of instances (e.g., a document could be represented as a bag of sentenc…
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi, Paolo Frasconi, Saverio Salzo +2
We introduce a framework based on bilevel programming that unifies gradient-based hyperparameter optimization and meta-learning. We show that an approximate version of the bilevel…
Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning
Luca Franceschi, Riccardo Grazzi, Massimiliano Pontil +2
In (Franceschi et al., 2018) we proposed a unified mathematical framework, grounded on bilevel programming, that encompasses gradient-based hyperparameter optimization and meta-lea…
Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres
Tijn Borghuis, Alessandro Tibo, Simone Conforti +3
We describe a system based on deep learning that generates drum patterns in the electronic dance music domain. Experimental results reveal that generated patterns can be employed t…