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Designing Effective Sparse Expert Models.

, , , , , , , и . CoRR, (2022)

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William Jórasz

William Masselink

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William Herz

 

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Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step., , , , , и . ICLR (Poster), OpenReview.net, (2018)Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity., , и . J. Mach. Learn. Res., (2022)Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts., , , , , , , , , и 10 other автор(ы). CoRR, (2023)Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?, , , , , , , , , и . EMNLP (Findings), стр. 12342-12364. Association for Computational Linguistics, (2023)Recall Traces: Backtracking Models for Efficient Reinforcement Learning., , , , , , и . CoRR, (2018)Disentangling the independently controllable factors of variation by interacting with the world., , , , , , , , и . CoRR, (2018)MaskGAN: Better Text Generation via Filling in the _______., , и . ICLR (Poster), OpenReview.net, (2018)Recall Traces: Backtracking Models for Efficient Reinforcement Learning., , , , , , , и . ICLR (Poster), OpenReview.net, (2019)Hyperbolic Discounting and Learning over Multiple Horizons, , , , и . (2019)cite arxiv:1902.06865.Deep Graph Infomax., , , , , и . ICLR (Poster), OpenReview.net, (2019)