According to our database1, Gavin Taylor authored at least 17 papers between 2008 and 2019.
Legend:Book In proceedings Article PhD thesis Other
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets.
Proceedings of the 36th International Conference on Machine Learning, 2019
Visualizing the Loss Landscape of Neural Nets.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Hoaxing statistical features of the Voynich Manuscript.
Adaptive Consensus ADMM for Distributed Optimization.
Proceedings of the 34th International Conference on Machine Learning, 2017
Scalable Classifiers with ADMM and Transpose Reduction.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017
Training Neural Networks Without Gradients: A Scalable ADMM Approach.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
Introduction to the Symposium on AI and the Mitigation of Human Error.
Proceedings of the 2016 AAAI Spring Symposia, 2016
Reports on the 2015 AAAI Spring Symposium Series.
AI Magazine, 2015
Layer-Specific Adaptive Learning Rates for Deep Networks.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy.
Proceedings of the 31th International Conference on Machine Learning, 2014
Towards Modeling the Behavior of Autonomous Systems and Humans for Trusted Operations.
Proceedings of the 2014 AAAI Spring Symposia, 2014
Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear Programs.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
An Intensive Introductory Robotics Course Without Prerequisites.
Proceedings of the Enabling Intelligence through Middleware, 2010
Kernelized value function approximation for reinforcement learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning.
Proceedings of the Machine Learning, 2008