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Simon Dufort-Labbé

PhD - Université de Montréal
Supervisor
Simon Lacoste-Julien
Research Topics
Machine Learning Theory

Publications

Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons
Simon Dufort-Labbé
Pierluca D'Oro
Evgenii Nikishin
Razvan Pascanu
Irina Rish
Pierre-Luc Bacon
Aristide Baratin
When training neural networks, dying neurons -- units becoming inactive or saturated -- are traditionally seen as harmful. This paper sheds … (see more)new light on this phenomenon. By exploring the impact of various hyperparameter configurations on dying neurons during training, we gather insights on how to improve upon sparse training approaches to pruning. We introduce Demon Pruning (DemP), a method that controls the proliferation of dead neurons through a combination of noise injection on active units and a one-cycle schedule regularization strategy, dynamically leading to network sparsity. Experiments on CIFAR-10 and ImageNet datasets demonstrate that DemP outperforms existing dense-to-sparse structured pruning methods, achieving better accuracy-sparsity tradeoffs and accelerating training by up to 3.56
2025-02-12
TMLR (accepted)
doi.org
openreview.net