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Understanding and correcting pathologies in the training of learned optimizers.

, , , , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4556-4565. PMLR, (2019)

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Jascha Sohl-Dickstein

Jascha Kehr

Jascha Melomedov

Michael Dickstein

Anja Sohl

 

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Parallel Training of Deep Networks with Local Updates., , , , , , , и . CoRR, (2020)Learning to Learn Without Labels., , , и . ICLR (Workshop), OpenReview.net, (2018)Explaining the Learning Dynamics of Direct Feedback Alignment., , , , и . ICLR (Workshop), OpenReview.net, (2017)REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models., , , , и . NIPS, стр. 2627-2636. (2017)Capacity and Trainability in Recurrent Neural Networks., , и . ICLR (Poster), OpenReview.net, (2017)Density estimation using Real NVP., , и . ICLR (Poster), OpenReview.net, (2017)Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies (Extended Abstract)., , и . IJCAI, стр. 5354-5358. ijcai.org, (2022)Fast Finite Width Neural Tangent Kernel., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 17018-17044. PMLR, (2022)Reverse engineering learned optimizers reveals known and novel mechanisms., , , , и . CoRR, (2020)Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers., , , , и . CoLLAs, том 199 из Proceedings of Machine Learning Research, стр. 142-164. PMLR, (2022)