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Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers.

L. Metz, C. Freeman, J. Harrison, N. Maheswaranathan, and J. Sohl-Dickstein. CoLLAs, volume 199 of Proceedings of Machine Learning Research, page 142-164. PMLR, (2022)

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Reverse engineering learned optimizers reveals known and novel mechanisms.N. Maheswaranathan, D. Sussillo, L. Metz, R. Sun, and J. Sohl-Dickstein. NeurIPS, page 19910-19922. (2021)Understanding How Encoder-Decoder Architectures Attend.K. Aitken, V. Ramasesh, Y. Cao, and N. Maheswaranathan. NeurIPS, page 22184-22195. (2021)Learning to Learn Without Labels.L. Metz, N. Maheswaranathan, B. Cheung, and J. Sohl-Dickstein. ICLR (Workshop), OpenReview.net, (2018)Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics.N. Maheswaranathan, A. Williams, M. Golub, S. Ganguli, and D. Sussillo. NeurIPS, page 15670-15679. (2019)Understanding and correcting pathologies in the training of learned optimizers.L. Metz, N. Maheswaranathan, J. Nixon, C. Freeman, and J. Sohl-Dickstein. ICML, volume 97 of Proceedings of Machine Learning Research, page 4556-4565. PMLR, (2019)Deep Learning Models of the Retinal Response to Natural Scenes.L. McIntosh, N. Maheswaranathan, A. Nayebi, S. Ganguli, and S. Baccus. NIPS, page 1361-1369. (2016)Universality and individuality in neural dynamics across large populations of recurrent networks.N. Maheswaranathan, A. Williams, M. Golub, S. Ganguli, and D. Sussillo. NeurIPS, page 15603-15615. (2019)Meta-Learning Update Rules for Unsupervised Representation Learning.L. Metz, N. Maheswaranathan, B. Cheung, and J. Sohl-Dickstein. ICLR, OpenReview.net, (2019)Recurrent Segmentation for Variable Computational Budgets.L. McIntosh, N. Maheswaranathan, D. Sussillo, and J. Shlens. CVPR Workshops, page 1648-1657. Computer Vision Foundation / IEEE Computer Society, (2018)From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction.H. Tanaka, A. Nayebi, N. Maheswaranathan, L. McIntosh, S. Baccus, and S. Ganguli. NeurIPS, page 8535-8545. (2019)

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Disambiguation of "Maheswaranathan, Niru"

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Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers.

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Disambiguation of "Maheswaranathan, Niru"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers.

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Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers.