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Training Neural Networks Without Gradients: A Scalable ADMM Approach.

G. Taylor, R. Burmeister, Z. Xu, B. Singh, A. Patel, and T. Goldstein. ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2722-2731. JMLR.org, (2016)

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Gavin Kane

Gavin Keighren

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Gavin Sim

Gavin Lowe

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An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning.R. Parr, L. Li, G. Taylor, C. Painter-Wakefield, and M. Littman. ICML, volume 307 of ACM International Conference Proceeding Series, page 752-759. ACM, (2008)Transferable Clean-Label Poisoning Attacks on Deep Neural Nets.C. Zhu, W. Huang, A. Shafahi, H. Li, G. Taylor, C. Studer, and T. Goldstein. CoRR, (2019)Robust Optimization as Data Augmentation for Large-scale Graphs.K. Kong, G. Li, M. Ding, Z. Wu, C. Zhu, B. Ghanem, G. Taylor, and T. Goldstein. CVPR, page 60-69. IEEE, (2022)LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition.V. Cherepanova, M. Goldblum, H. Foley, S. Duan, J. Dickerson, G. Taylor, and T. Goldstein. ICLR, OpenReview.net, (2021)Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes.M. Petrik, G. Taylor, R. Parr, and S. Zilberstein. ICML, page 871-878. Omnipress, (2010)Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction.T. Goldstein, G. Taylor, K. Barabin, and K. Sayre. AISTATS, volume 51 of JMLR Workshop and Conference Proceedings, page 1151-1158. JMLR.org, (2016)Introduction to the Symposium on AI and the Mitigation of Human Error.R. Mittu, G. Taylor, D. Sofge, and W. Lawless. AAAI Spring Symposia, AAAI Press, (2016)An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy.G. Taylor, C. Geer, and D. Piekut. ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 451-459. JMLR.org, (2014)Transferable Clean-Label Poisoning Attacks on Deep Neural Nets.C. Zhu, W. Huang, H. Li, G. Taylor, C. Studer, and T. Goldstein. ICML, volume 97 of Proceedings of Machine Learning Research, page 7614-7623. PMLR, (2019)Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning.A. Murad, F. Kraemer, K. Bach, and G. Taylor. SASO, page 43-51. IEEE, (2019)

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Disambiguation of "Taylor, Gavin"

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Training Neural Networks Without Gradients: A Scalable ADMM Approach.

Please choose a person to relate this publication to

Gavin Kane

Gavin Keighren

Gavin Brown

Gavin Sim

Gavin Lowe

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Taylor, Gavin"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Training Neural Networks Without Gradients: A Scalable ADMM Approach.

Please choose a person to relate this publication to

Gavin Kane

Gavin Keighren

Gavin Brown

Gavin Sim

Gavin Lowe

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Chicago
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Training Neural Networks Without Gradients: A Scalable ADMM Approach.