Successive Halving Top-k Operator
نویسندگان
چکیده
We propose a differentiable successive halving method of relaxing the top-k operator, rendering gradient-based optimization possible. The need to perform softmax iteratively on entire vector scores is avoided using tournament-style selection. As result, much better approximation and lower computational cost achieved compared previous approach.
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2021
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v35i18.17931