J. Zico Kolter
According to our database^{1},
J. Zico Kolter
authored at least 57 papers
between 2003 and 2018.
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Bibliography
2018
Differentiable MPC for Endtoend Planning and Control.
CoRR, 2018
A ContinuousTime View of Early Stopping for Least Squares Regression.
CoRR, 2018
Trellis Networks for Sequence Modeling.
CoRR, 2018
Scaling provable adversarial defenses.
CoRR, 2018
What game are we playing? Endtoend learning in normal and extensive form games.
CoRR, 2018
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.
CoRR, 2018
What Game Are We Playing? Endtoend Learning in Normal and Extensive Form Games.
Proceedings of the TwentySeventh International Joint Conference on Artificial Intelligence, 2018
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope.
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Provable defenses against adversarial examples via the convex outer adversarial polytope.
CoRR, 2017
Intelligent Pothole Detection and Road Condition Assessment.
CoRR, 2017
The Mixing method: coordinate descent for lowrank semidefinite programming.
CoRR, 2017
Gradient descent GAN optimization is locally stable.
CoRR, 2017
Taskbased Endtoend Model Learning.
CoRR, 2017
OptNet: Differentiable Optimization as a Layer in Neural Networks.
CoRR, 2017
Gradient descent GAN optimization is locally stable.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Taskbased Endtoend Model Learning in Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Input Convex Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017
OptNet: Differentiable Optimization as a Layer in Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017
A Semismooth Newton Method for Fast, Generic Convex Programming.
Proceedings of the 34th International Conference on Machine Learning, 2017
Polynomial Optimization Methods for Matrix Factorization.
Proceedings of the ThirtyFirst AAAI Conference on Artificial Intelligence, 2017
2016
Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control.
Rel. Eng. & Sys. Safety, 2016
Input Convex Neural Networks.
CoRR, 2016
Computational approaches for efficient scheduling of steel plants as demand response resource.
Proceedings of the Power Systems Computation Conference, 2016
The Multiple Quantile Graphical Model.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Epigraph projections for fast general convex programming.
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization.
Proceedings of the ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
An SVD and Derivative Kernel Approach to Learning from Geometric Data.
Proceedings of the TwentyNinth AAAI Conference on Artificial Intelligence, 2015
An Additive Autoregressive Hidden Markov Model for Energy Disaggregation.
Proceedings of the Computational Sustainability, 2015
2014
Fast Newton methods for the group fused lasso.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014
Contextually Supervised Source Separation with Application to Energy Disaggregation.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
2013
Contextually Supervised Source Separation with Application to Energy Disaggregation.
CoRR, 2013
A Fast Algorithm for Sparse Controller Design.
CoRR, 2013
A moving horizon state estimator in the control of thermostatically controlled loads for demand response.
Proceedings of the IEEE Fourth International Conference on Smart Grid Communications, 2013
Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting.
Proceedings of the 30th International Conference on Machine Learning, 2013
Largescale probabilistic forecasting in energy systems using sparse Gaussian conditional random fields.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
2012
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Design, analysis, and learning control of a fully actuated micro wind turbine.
Proceedings of the American Control Conference, 2012
2011
The Stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion.
I. J. Robotics Res., 2011
The Fixed Points of OffPolicy TD.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
Towards fully autonomous driving: Systems and algorithms.
Proceedings of the IEEE Intelligent Vehicles Symposium (IV), 2011
A LargeScale Study on Predicting and Contextualizing Building Energy Usage.
Proceedings of the TwentyFifth AAAI Conference on Artificial Intelligence, 2011
2010
Energy Disaggregation via Discriminative Sparse Coding.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
A probabilistic approach to mixed openloop and closedloop control, with application to extreme autonomous driving.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010
2009
Policy search via the signed derivative.
Proceedings of the Robotics: Science and Systems V, University of Washington, Seattle, USA, June 28, 2009
Taskspace trajectories via cubic spline optimization.
Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009
Stereo vision and terrain modeling for quadruped robots.
Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009
Regularization and feature selection in leastsquares temporal difference learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
NearBayesian exploration in polynomial time.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
2008
A control architecture for quadruped locomotion over rough terrain.
Proceedings of the 2008 IEEE International Conference on Robotics and Automation, 2008
Spaceindexed dynamic programming: learning to follow trajectories.
Proceedings of the Machine Learning, 2008
2007
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts.
Journal of Machine Learning Research, 2007
Learning omnidirectional path following using dimensionality reduction.
Proceedings of the Robotics: Science and Systems III, 2007
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
2006
Learning to Detect and Classify Malicious Executables in the Wild.
Journal of Machine Learning Research, 2006
2005
Using additive expert ensembles to cope with concept drift.
Proceedings of the Machine Learning, 2005
2004
Learning to detect malicious executables in the wild.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004
2003
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003