48 citations · 140 across the 16 of their papers we have counts for
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cs.LG2021
Structured Ensembles: an Approach to Reduce the Memory Footprint of Ensemble Methods
Jary Pomponi, Simone Scardapane, Aurelio Uncini
In this paper, we propose a novel ensembling technique for deep neural networks, which is able to drastically reduce the required memory compared to alternative approaches. In part…
cs.LG2021
Avalanche: an End-to-End Library for Continual Learning
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu +25
Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning. Recently, we have witnessed a renewed and fast-growing…