J. Zico Kolter

According to our database1, J. Zico Kolter authored at least 57 papers between 2003 and 2018.

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Bibliography

2018
Differentiable MPC for End-to-end Planning and Control.
CoRR, 2018

A Continuous-Time 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? End-to-end 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? End-to-end Learning in Normal and Extensive Form Games.
Proceedings of the Twenty-Seventh 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 low-rank semidefinite programming.
CoRR, 2017

Gradient descent GAN optimization is locally stable.
CoRR, 2017

Task-based End-to-end 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

Task-based End-to-end 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 Thirty-First 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 Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

An SVD and Derivative Kernel Approach to Learning from Geometric Data.
Proceedings of the Twenty-Ninth 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 Twenty-Eighth 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

Large-scale 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 Off-Policy 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 12-14 December 2011, 2011

Towards fully autonomous driving: Systems and algorithms.
Proceedings of the IEEE Intelligent Vehicles Symposium (IV), 2011

A Large-Scale Study on Predicting and Contextualizing Building Energy Usage.
Proceedings of the Twenty-Fifth 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 6-9 December 2010, 2010

A probabilistic approach to mixed open-loop and closed-loop 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

Task-space 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 least-squares temporal difference learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Near-Bayesian 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

Space-indexed 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


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