A Survey of Lottery Ticket Hypothesis
CoRR(2024)
摘要
The Lottery Ticket Hypothesis (LTH) states that a dense neural network model
contains a highly sparse subnetwork (i.e., winning tickets) that can achieve
even better performance than the original model when trained in isolation.
While LTH has been proved both empirically and theoretically in many works,
there still are some open issues, such as efficiency and scalability, to be
addressed. Also, the lack of open-source frameworks and consensual experimental
setting poses a challenge to future research on LTH. We, for the first time,
examine previous research and studies on LTH from different perspectives. We
also discuss issues in existing works and list potential directions for further
exploration. This survey aims to provide an in-depth look at the state of LTH
and develop a duly maintained platform to conduct experiments and compare with
the most updated baselines.
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