The Lottery Ticket Hypothesis¶
Frankle, J., & Carbin, M. (2019). The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. Proceedings of ICLR 2019.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Pruning
- Machine learning — magnitude and structured pruning, the lottery-ticket hypothesis, model compression; cost-complexity pruning in decision trees; alpha-beta and branch-and-bound pruning in search.
This sourceShows a high-performing sparse subnetwork can be found only after training the dense over-parameterized network, then pruning.
- Machine learning — magnitude and structured pruning, the lottery-ticket hypothesis, model compression; cost-complexity pruning in decision trees; alpha-beta and branch-and-bound pruning in search.
Verification¶
Does it exist? Not checked yet. This entry carries no identifier to resolve. It was extracted from the citation as written in the article, normalized, and deduplicated against the rest of the registry.
Does it back the claim? Not recorded. The single citation of this work carries no recorded support check.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:1ca178e87059 · see in the full table