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When Layers Play the Lottery, all Tickets Win at Initialization
March 20, 2024, 4:43 a.m. | Artur Jordao, George Correa de Araujo, Helena de Almeida Maia, Helio Pedrini
cs.LG updates on arXiv.org arxiv.org
Abstract: Pruning is a standard technique for reducing the computational cost of deep networks. Many advances in pruning leverage concepts from the Lottery Ticket Hypothesis (LTH). LTH reveals that inside a trained dense network exists sparse subnetworks (tickets) able to achieve similar accuracy (i.e., win the lottery - winning tickets). Pruning at initialization focuses on finding winning tickets without training a dense network. Studies on these concepts share the trend that subnetworks come from weight or …
abstract accuracy advances arxiv computational concepts cost cs.lg hypothesis inside lottery ticket hypothesis network networks pruning standard tickets type
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