2020

Multiscale Deep Equilibrium Models
Shaojie Bai, Vladlen Koltun, J. Zico Kolter
In Neural Information Processing Systems, 2020 
Monotone operator equilibrium networks
Ezra Winston, J. Zico Kolter
In Neural Information Processing Systems, 2020 
Denoised Smoothing: A Provable Defense for Pretrained Classifiers
Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter
In Neural Information Processing Systems, 2020 
Community detection using fast lowcardinality semidefinite programmingâ€©
PoWei Wang, J. Zico Kolter
In Neural Information Processing Systems, 2020 
Efficient semidefiniteprogrammingbased inference for binary and multiclass MRFs
Chirag Pabbaraju, PoWei Wang, J. Zico Kolter
In Neural Information Processing Systems, 2020 
Deep Archimedean Copulas
Chun Kai Ling, Fei Fang, J. Zico Kolter
In Neural Information Processing Systems, 2020 
Overfitting in adversarially robust deep learning
Leslie Rice, Eric Wong, J. Zico Kolter
In International Conference on Machine Learning, 2020 
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
Filipe de Avila BelbutePeres, Thomas D. Economon, J. Zico Kolter
In International Conference on Machine Learning, 2020 
Adversarial robustness against the union of multiple perturbation models
Pratyush Maini, Eric Wong, J. Zico Kolter
In International Conference on Machine Learning, 2020 
Certified Robustness to LabelFlipping Attacks via Randomized Smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, J. Zico Kolter
In International Conference on Machine Learning, 2020 
APPerf: Incorporating Generic Performance Metrics in Differentiable Learning
Rizal Fathony, J. Zico Kolter
In International Conference on AI and Statistics, 2020 
Fast is better than free: Revisiting adversarial training
Eric Wong, Leslie Rice, J. Zico Kolter
In International Conference on Learning Representations, 2020 
Differentiable learning of numerical rules in knowledge graphs
PoWei Wang, Daria Stepanova, Csaba Domokos, and J. Zico Kolter
In International Conference on Learning Representations, 2020 
A Framework for Robustness Certification of Smoothed Classifiers Using fDivergences
Krishnamurthy (Dj) Dvijotham, Jamie Hayes, Borja Balle, J. Zico Kolter, Chongli Qin, Andras Gyorgy, Kai Xiao, Sven Gowal, Pushmeet Kohli
In International Conference on Learning Representations, 2020
2019

Uniform convergence may be unable to explain generalization in deep learning
Vaishnavh Nagarajan, J. Zico Kolter
In Neural Information Processing Systems, 2019 
Deep equilibrium models
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
In Neural Information Processing Systems, 2019 
Differentiable Convex Optimization Layers
Akshay Agrawal, Brandon Amos, Shane Barratt, Stephen Boyd, Steven Diamond, J. Zico Kolter
In Neural Information Processing Systems, 2019 
Adversarial Music: Real World Audio Adversary Against Wakeword Detection Systems
Juncheng Li, Shuhui Qu, Xinjian Li, Joseph Szurley, J. Zico Kolter, Florian Metze
In Neural Information Processing Systems, 2019 
Learning Stable Deep Dynamics Models
Gaurav Manek, Zico Kolter
In Neural Information Processing Systems, 2019 
Computational Sustainability: Computing for a Better World and a Sustainable Future
Carla Gomes et al.
In Communications of the ACM, 2019 
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
PoWei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter
In International Conference on Machine Learning, 2019 
Adversarial camera stickers: A physical camerabased attack on deep learning systems
Juncheng Li, Frank R. Schmidt, J. Zico Kolter
In International Conference on Machine Learning, 2019 
Certified adversarial robustness via randomized smoothing
Jeremy M Cohen, Elan Rosenfeld, J. Zico Kolter
In International Conference on Machine Learning, 2019 
Wasserstein adversarial examples via projected Sinkhorn iterations
Eric Wong, Frank R. Schmidt, J. Zico Kolter
In International Conference on Machine Learning, 2019 
Trellis networks for sequence modeling
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
In International Conference on Learning Representations, 2019 
Deterministic PACBayesian generalization bounds for deep networks via generalizing noiseresilience
Vaishnavh Nagarajan, J. Zico Kolter
In International Conference on Learning Representations, 2019 
A continuoustime view of early stopping for least squares regression
Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani
In AI and Statistics, 2019 
Large scale learning of agent rationality in twoplayer zerosum games
Chun Kai Ling, Fei Fang, J. Zico Kolter
In AAAI, 2019 
Lowrank semidefinite programming for the MAX2SAT problem
PoWei Wang, J. Zico Kolter
In AAAI, 2019
2018

Endtoend differentiable physics for learning and control
Filipe de A. BelbutePeres, Kevin A. Smith, Kelsey R. Allen, Joshua B. Tenenbaum, J. Zico Kolter
In Neural Information Processing Systems (NeurIPS), 2018 
Scaling provable adversarial defenses
Eric Wong, Frank Schmidt, Jan Hendrik Metzen, J. Zico Kolter
In Neural Information Processing Systems (NeurIPS), 2018 
Differentiable MPC for endtoend planning and control
Brandon Amos, Ivan Dario Jimenez Rodriguez, Jacob Sacks, Byron Boots, J. Zico Kolter
In Neural Information Processing Systems (NeurIPS), 2018 
The Mixing method: coordinate descent for lowrank semidefinite programming
PoWei Wang, WeiCheng Chang, J. Zico Kolter
Preprint 
Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong, J. Zico Kolter
In Proceedings of the International Conference on Machine Learning (ICML), 2018 
What game are we playing? Endtoend learning in normal and extensive form games
Chun Kai Ling, Fei Fang, J. Zico Kolter
International Joint Conference on Artificial Intelligence (IJCAI), 2018 
An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
Preprint
2017

Gradient descent GAN optimization is locally stable
Vaishnavh Nagarajan, J. Zico Kolter
In Neural Information Processing Systems, 2017 
Taskbased Endtoend Model Learning in Stochastic Optimization
Priya Donti, Brandon Amos, J. Zico Kolter
In Neural Information Processing Systems, 2017 
A Semismooth Newton Method for Fast, Generic Convex Programming
Alnur Ali, Eric Wong, J. Zico Kolter
In Proceedings of the International Conference on Machine Learning (ICML), 2017 
OptNet: Differentiable Optimization as a Layer in Neural Networks
Brandon Amos, J. Zico Kolter
In Proceedings of the International Conference on Machine Learning (ICML), 2017 
Input Convex Neural Networks
Brandon Amos, Lei Xu, J. Zico Kolter
In Proceedings of the International Conference on Machine Learning (ICML), 2017 
Polynomial optimization methods for matrix factorization
PoWei Wang, ChunLiang Li, J. Zico Kolter
In Proceedings of the Conference on Artificial Intelligence (AAAI), 2017
2016

The Multiple Quantile Graphical Model
Alnur Ali, J. Zico Kolter, Ryan Tibshirani
In Neural Information Processing Systems, 2016 
Model order reduction using sparse coding exemplified for the liddriven cavity
Rohit Deshmukh, Jack J. McNamara, Zongxian Liang, J. Zico Kolter, Abhijit Gogulapati
In Journal of Fluid Mechanics (2016), Vol 808, pp. 189â€“223. 
Epigraph projections for fast general convex programming
Powei Wang, Matt Wytock, J. Zico Kolter
In Proceedings of the International Conference on Machine Learning (ICML), 2016 
Model Predictive Control of Industrial Loads and Energy Storage for Demand Response
Xiao Zhang, Gabriela Hug, Zico Kolter, Iiro Harjunkoski
In IEEE PES General Meeting (PESGM), 2016, (Best conference paper award) 
Computational Approaches for Efficient Scheduling of Steel Plants
Xiao Zhang, Gabriela Hug, Zico Kolter, Iiro Harjunkoski
In IEEE Power System Computation Conference (PSCC), 2016
2015

Convex programming with fast proximal and linear operators, (Epsilon software)
Matt Wytock, Powei Wang, J. Zico Kolter. Preprint. 
Industrial Demand Response by Steel Plants with Spinning Reserve Provision
Xiao Zhang, Gabriela Hug, Zico Kolter, Iiro Harjunkoski
In IEEE North American Power Symposium (NAPS), 2015 
Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization
Alnur Ali, J. Zico Kolter, Steven Diamond, Stephen Boyd
In Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI), 2015 
An SVD and Derivative Kernel Approach to Learning from Geometric Data
Eric Wong, J. Zico Kolter
In Proceedings of the Conference on Artificial Intelligence (AAAI), 2015
2014

Fast Newton Methods for the Group Fused Lasso
Matt Wytock, Suvrit Sra, J. Zico Kolter
In Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI), 2014 
Contextually Supervised Source Separation with Application to Energy Disaggregation
Matt Wytock, J. Zico Kolter
In Proceedings of the Conference on Artificial Intelligence (AAAI), Computational Sustainability Track, 2014 
Optimal Planning and Learning in Uncertain Environments for Management of Wind Farms
Milad Memarzadeh, Matteo Pozzi, J. Zico Kolter
To appear in Journal of Computing in Civil Engineering, 2014 
A Fast Algorithm for Sparse Controller Design
Matt Wytock, J. Zico Kolter, 2014
2013

Largescale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields
Matt Wytock, J. Zico Kolter
In Proceedings of the IEEE Conference on Decision and Control, 2013 
A Moving Window State Estimator in the Control of Thermostatically Controlled Loads for Demand Response
Emre Can Kara, J. Zico Kolter, Mario Berges, Bruce Krogh, Gabriela Hug and Tugce Yuksel
In Proceedings of the IEEE SmartGridComm, 2013 
Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting
Matt Wytock, J. Zico Kolter
In Proceedings of the International Conference on Machine Learning, 2013
2012

Design, Analysis, and Learning Control of a Fully Actuated Micro Wind Turbine
J. Zico Kolter, Zachary Jackowski, Russ Tedrake
In Proceedings of the American Control Conference, 2012 
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
J. Zico Kolter, Tommi Jaakkola
In Proceedings of the International Conference on Artificial Intelligence and Statistics, 2012
2011

The Fixed Points of OffPolicy TD
J. Zico Kolter
In Neural Information Processing Systems, 2011 
REDD: A Public Data Set for Energy Disaggregation Research
J. Zico Kolter, Matthew J. Johnson
In Proceedings of the SustKDD Workshop on Data Mining Appliations in Sustainbility, 2011 
A LargeScale Study on Predicting and Contextualizing Building Energy Usage
J. Zico Kolter, Joseph Ferreira
In Proceedings of the Conference on Artificial Intelligence (AAAI), Special Track on Computational Sustainability and AI, 2011 
Camerabased Localization for Autonomous UAV Formation Flight
Zouhair Mahboubi, J. Zico Kolter, Tao Wang, Geoffrey Bower, Andrew Y. Ng
In Proceedings of the AIAA@Infotech Conference, 2011 
Towards Fully Autonomous Driving: Systems and Algorithms
Jesse Levinson, Jake Askeland, Jan Becker, Jennifer Dolson, David Held, Soren Kammel, J. Zico Kolter, Dirk Langer, Oliver Pink, Vaughan Ronald Pratt, Michael Sokolsky, Ganymed Stanek, David Michael Stavens, Alex Teichman, Moritz Werling, Sebastian Thrun
In Proceedings of the Intelligent Vehicles Symposium, 2011 
The Stanford LittleDog: A Learning and Rapid Replanning Approach to Quadruped Locomotion
J. Zico Kolter, Andrew Y. Ng
In International Journal of Robotics Research 30 (2), 2011
2010

Learning and Control with Inaccurate Models
J. Zico Kolter
Ph.D. Thesis, Stanford University, 2010 
Energy Disaggregation via Discriminative Sparse Coding
J. Zico Kolter, Siddharth Batra, Andrew Y. Ng
In Neural Information Processing Systems, 2010 
A Probabilistic Approach to Mixed Openloop and Closedloop Control, with Application to Extreme Autonomous Driving
J. Zico Kolter, Christian Plagemann, David T. Jackson, Andrew Y. Ng, Sebastian Thrun
In Proceedings of the International Conference on Robotics and Automation, 2010
2009

Policy Search via the Signed Derivative
J. Zico Kolter, Andrew Y. Ng
In Proceedings of Robotics: Science and Systems, 2009 
NearBayesian Exploration in Polynomial Time
J. Zico Kolter, Andrew Y. Ng
In Proceedings of the International Conference on Machine Learning, 2009 
Regularization and Feature Selection in LeastSquares Temporal Difference Learning
J. Zico Kolter, Andrew Y. Ng
In Proceedings of the International Conference on Machine Learning, 2009 
TaskSpace Trajectories via Cubic Spline Optimization
J. Zico Kolter, Andrew Y. Ng
In Proceedings of the International Conference on Robotics and Automation, 2009 
Stereo Vision and Terrain Modeling for Quadruped Robots
J. Zico Kolter, Youngjun Kim, Andrew Y. Ng
In Proceedings of the International Conference on Robotics and Automation, 2009
2008

Spaceindexed Dynamic Programming: Learning to Follow Trajectories
J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, Charles DuHadway
In Proceedings of the International Conference on Robotics and Automation, 2008 
A Control Architecture for Quadruped Locomotion Over Rough Terrain
J. Zico Kolter, Mike P. Rodgers, Andrew Y. Ng
In Proceedings of the International Conference on Robotics and Automation, 2008
2007

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion
J. Zico Kolter, Pieter Abbeel, Andrew Y. Ng
In Neural Information Processing Systems, 2007 
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
J. Zico Kolter, Marcus A. Maloof
In Journal of Machine Learning Research 8, 2007 
Learning Omnidirectional Path Following Using Dimensionality Reduction
J. Zico Kolter, Andrew Y. Ng
In Proceedings of Robotics: Science and Systems, 2007
2006
 Learning to Detect and Classify Malicious Executables in the Wild
J. Zico Kolter, Marcus A. Maloof
In Journal of Machine Learning Research (Special Issues on Machine Learning in Computer Security) 7, 2006
2005
 Using Additive Expert Ensembles to Cope with Concept Drift
J. Zico Kolter, Marcus A. Maloof
In Proceedings of the International Conference on Machine Learning, 2005
2004
 Learning to Detect Malicious Executables in the Wild
Jeremy Z. Kolter, Marcus A. Maloof
In Proceedings of the International Conference on Knowledge Discovery and Data Mining, 2004
2003
 Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Jeremy Z. Kolter, M. A. Maloof
In Proceedings of the International Conference on Data Mining, 2003