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DSD: Dense-Sparse-Dense Training for Deep Neural Networks., , , , , , , , , и 2 other автор(ы). ICLR (Poster), OpenReview.net, (2017)Poster reception - N-Body simulation on GPUs., , , , , и . SC, стр. 188. ACM Press, (2006)An empirical analysis of compute-optimal large language model training., , , , , , , , , и 12 other автор(ы). NeurIPS, (2022)N-Body Simulations on GPUs, , , , , и . CoRR, (2007)Improving language models by retrieving from trillions of tokens, , , , , , , , , и 18 other автор(ы). (2021)cite arxiv:2112.04426Comment: Fix incorrect reported numbers in Table 14.Improving Language Models by Retrieving from Trillions of Tokens., , , , , , , , , и 18 other автор(ы). ICML, том 162 из Proceedings of Machine Learning Research, стр. 2206-2240. PMLR, (2022)The State of Sparse Training in Deep Reinforcement Learning., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 7766-7792. PMLR, (2022)Practical Real Time Recurrent Learning with a Sparse Approximation., , , , , и . ICLR, OpenReview.net, (2021)Mixed Precision Training, , , , , , , , , и 1 other автор(ы). (2017)cite arxiv:1710.03740Comment: Published as a conference paper at ICLR 2018.Rigging the Lottery: Making All Tickets Winners., , , , и . CoRR, (2019)