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Training Neural Networks Without Gradients: A Scalable ADMM Approach.

, , , , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2722-2731. JMLR.org, (2016)

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Towards Modeling the Behavior of Autonomous Systems and Humans for Trusted Operations., , , , , , and . AAAI Spring Symposia, AAAI Press, (2014)Visualizing the Loss Landscape of Neural Nets, , , , and . (2017)Visualizing the Loss Landscape of Neural Nets., , , , and . NeurIPS, page 6391-6401. (2018)IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning., , , and . IOT, page 37:1-37:4. ACM, (2019)Transferable Clean-Label Poisoning Attacks on Deep Neural Nets., , , , , , and . CoRR, (2019)Robust Optimization as Data Augmentation for Large-scale Graphs., , , , , , , and . CVPR, page 60-69. IEEE, (2022)LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition., , , , , , and . ICLR, OpenReview.net, (2021)An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning., , , , and . ICML, volume 307 of ACM International Conference Proceeding Series, page 752-759. ACM, (2008)Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes., , , and . ICML, page 871-878. Omnipress, (2010)An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy., , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 451-459. JMLR.org, (2014)