Publications

2024

• Rethinking LLM Memorization through the Lens of Adversarial Compression
  Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C Lipton, J Zico Kolter
  arXiv preprint arXiv:2404.15146, 2024

• Forcing Diffuse Distributions out of Language Models
  Yiming Zhang, Avi Schwarzschild, Nicholas Carlini, Zico Kolter, Daphne Ippolito
  arXiv preprint arXiv:2404.10859, 2024

• Massive Activations in Large Language Models
  Mingjie Sun, Xinlei Chen, J Zico Kolter, Zhuang Liu
  arXiv preprint arXiv:2402.17762, 2024

• Tofu: A task of fictitious unlearning for llms
  Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C Lipton, J Zico Kolter
  arXiv preprint arXiv:2401.06121, 2024

• Scaling Laws for Data Filtering–Data Curation cannot be Compute Agnostic
  Sachin Goyal, Pratyush Maini, Zachary C Lipton, Aditi Raghunathan, J Zico Kolter
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

• DART: Implicit Doppler Tomography for Radar Novel View Synthesis
  Tianshu Huang, John Miller, Akarsh Prabhakara, Tao Jin, Tarana Laroia, Zico Kolter, Anthony Rowe
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

• Computing Low-Entropy Couplings for Large-Support Distributions
  Samuel Sokota, Dylan Sam, Christian Schroeder de Witt, Spencer Compton, Jakob Nicolaus Foerster, J Zico Kolter
  Conference on Uncertainty in Artificial Intelligence, 2024

• Understanding prompt engineering may not require rethinking generalization
  Victor Akinwande, Yiding Jiang, Dylan Sam, J Zico Kolter
  International Conference on Learning Representations, 2024

• Manifold preserving guided diffusion
  Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, others
  International Conference on Learning Representations, 2024

• Why is SAM Robust to Label Noise?
  Christina Baek, Zico Kolter, Aditi Raghunathan
  International Conference on Learning Representations, 2024

• T-mars: Improving visual representations by circumventing text feature learning
  Pratyush Maini, Sachin Goyal, Zachary C Lipton, J Zico Kolter, Aditi Raghunathan
  International Conference on Learning Representations, 2024

• A simple and effective pruning approach for large language models
  Mingjie Sun, Zhuang Liu, Anna Bair, J Zico Kolter
  International Conference on Learning Representations, 2024

• On the Joint Interaction of Models, Data, and Features
  Yiding Jiang, Christina Baek, J Zico Kolter
  International Conference on Learning Representations, 2024

• The Update Equivalence Framework for Decision-Time Planning
  Samuel Sokota, Gabriele Farina, David J Wu, Hengyuan Hu, Kevin A Wang, J Zico Kolter, Noam Brown
  International Conference on Learning Representations, 2024

• Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation
  Runtian Zhai, Bingbin Liu, Andrej Risteski, Zico Kolter, Pradeep Ravikumar
  International Conference on Learning Representations, 2024

• Predicting the Performance of Foundation Models via Agreement-on-the-Line
  Aman Mehra, Rahul Saxena, Taeyoun Kim, Christina Baek, Zico Kolter, Aditi Raghunathan
  arXiv preprint arXiv:2404.01542, 2024

• Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation
  Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J Zico Kolter
  arXiv preprint arXiv:2403.19103, 2024

• Bayesian Neural Networks with Domain Knowledge Priors
  Dylan Sam, Rattana Pukdee, Daniel P Jeong, Yewon Byun, J Zico Kolter
  arXiv preprint arXiv:2402.13410, 2024

• AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs
  Victor Akinwande, J Zico Kolter
  arXiv preprint arXiv:2403.03772, 2024

• An Axiomatic Approach to Model-Agnostic Concept Explanations
  Zhili Feng, Michal Moshkovitz, Dotan Di Castro, J Zico Kolter
  arXiv preprint arXiv:2401.06890, 2024

2023

• Learning with Explanation Constraints
  Rattana Pukdee, Dylan Sam, J Zico Kolter, Maria-Florina F Balcan, Pradeep Ravikumar
  Advances in Neural Information Processing Systems, 2023

• One-step diffusion distillation via deep equilibrium models
  Zhengyang Geng, Ashwini Pokle, J Zico Kolter
  Advances in Neural Information Processing Systems, 2023

• Deep Equilibrium Based Neural Operators for Steady-State PDEs
  Tanya Marwah, Ashwini Pokle, J Zico Kolter, Zachary Lipton, Jianfeng Lu, Andrej Risteski
  Advances in Neural Information Processing Systems, 2023

• Language models are weak learners
  Hariharan Manikandan, Yiding Jiang, J Zico Kolter
  Advances in Neural Information Processing Systems, 2023

• On the importance of exploration for generalization in reinforcement learning
  Yiding Jiang, J Zico Kolter, Roberta Raileanu
  Advances in Neural Information Processing Systems, 2023

• Neural functional transformers
  Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J Zico Kolter, Chelsea Finn
  Advances in Neural Information Processing Systems, 2023

• Permutation equivariant neural functionals
  Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J Zico Kolter, Chelsea Finn
  Advances in Neural Information Processing Systems, 2023

• Provably bounding neural network preimages
  Suhas Kotha, Christopher Brix, J Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang
  Advances in Neural Information Processing Systems, 2023

• Representation engineering: A top-down approach to ai transparency
  Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, others
  arXiv preprint arXiv:2310.01405, 2023

• Universal and transferable adversarial attacks on aligned language models
  Andy Zou, Zifan Wang, J Zico Kolter, Matt Fredrikson
  arXiv preprint arXiv:2307.15043, 2023

• Model-tuning Via Prompts Makes NLP Models Adversarially Robust
  Mrigank Raman, Pratyush Maini, J Zico Kolter, Zachary C Lipton, Danish Pruthi
  Empirical Methods in Natural Language Processing, 2023

• Deep Off-Policy Iterative Learning Control
  Swaminathan Gurumurthy, J Zico Kolter, Zachary Manchester
  Learning for Dynamics and Control Conference, 2023

• Practical Critic Gradient based Actor Critic for On-Policy Reinforcement Learning
  Swaminathan Gurumurthy, Zachary Manchester, J Zico Kolter
  Learning for Dynamics and Control Conference, 2023

• Can neural network memorization be localized?
  Pratyush Maini, Michael C Mozer, Hanie Sedghi, Zachary C Lipton, J Zico Kolter, Chiyuan Zhang
  International Conference on Machine Learning, 2023

• Abstracting imperfect information away from two-player zero-sum games
  Samuel Sokota, Ryan D’Orazio, Chun Kai Ling, David J Wu, J Zico Kolter, Noam Brown
  International Conference on Machine Learning, 2023

• Mimetic initialization of self-attention layers
  Asher Trockman, J Zico Kolter
  International Conference on Machine Learning, 2023

• Single image backdoor inversion via robust smoothed classifiers
  Mingjie Sun, Zico Kolter
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

• Finetune like you pretrain: Improved finetuning of zero-shot vision models
  Sachin Goyal, Ananya Kumar, Sankalp Garg, Zico Kolter, Aditi Raghunathan
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

• Function approximation for solving stackelberg equilibrium in large perfect information games
  Chun Kai Ling, J Zico Kolter, Fei Fang
  Proceedings of the AAAI Conference on Artificial Intelligence, 2023

• Losses over labels: Weakly supervised learning via direct loss construction
  Dylan Sam, J Zico Kolter
  Proceedings of the AAAI Conference on Artificial Intelligence, 2023

• Adversarial robustness in discontinuous spaces via alternating sampling \& descent
  Rahul Venkatesh, Eric Wong, Zico Kolter
  Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

• Projected Off-Policy Q-Learning (POP-QL) for Stabilizing Offline Reinforcement Learning
  Melrose Roderick, Gaurav Manek, Felix Berkenkamp, J Zico Kolter
  arXiv preprint arXiv:2311.14885, 2023

• Torchdeq: A library for deep equilibrium models
  Zhengyang Geng, J Zico Kolter
  arXiv preprint arXiv:2310.18605, 2023

• Reliable Test-Time Adaptation via Agreement-on-the-Line
  Eungyeup Kim, Mingjie Sun, Aditi Raghunathan, Zico Kolter
  arXiv preprint arXiv:2310.04941, 2023

• Importance of equivariant and invariant symmetries for fluid flow modeling
  Varun Shankar, Shivam Barwey, Zico Kolter, Romit Maulik, Venkatasubramanian Viswanathan
  arXiv preprint arXiv:2307.05486, 2023

• Leveraging multiple descriptive features for robust few-shot image learning
  Zhili Feng, Anna Bair, J Zico Kolter
  arXiv preprint arXiv:2307.04317, 2023

• Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport
  Mukul Bhutani, J Zico Kolter
  arXiv preprint arXiv:2303.07675, 2023

• Localized text-to-image generation for free via cross attention control
  Yutong He, Ruslan Salakhutdinov, J Zico Kolter
  arXiv preprint arXiv:2306.14636, 2023

2022

• Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift
  Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter
  In Neural Information Processing Systems (NeurIPS), 2022

• Deep Equilibrium Approaches to Diffusion Models
  Ashwini Pokle, Zhengyang Geng, J. Zico Kolter
  In Neural Information Processing Systems (NeurIPS), 2022

• Characterizing Datapoints via Second-Split Forgetting
  Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter
  In Neural Information Processing Systems (NeurIPS), 2022

• The Pitfalls of Regularization in Off-Policy TD Learning
  Gaurav Manek, J. Zico Kolter
  In Neural Information Processing Systems (NeurIPS), 2022

• Test Time Adaptation via Conjugate Pseudo-labels
  Sachin Goyal, Mingjie Sun, Aditi Raghunathan, J. Zico Kolter
  In Neural Information Processing Systems (NeurIPS), 2022

• Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
  Cem Anil*, Ashwini Pokle*, Kaiqu Liang*, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger Baker Grosse
  In Neural Information Processing Systems (NeurIPS), 2022

• General Cutting Planes for Bound-Propagation-Based Neural Network Verification
  Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
  In Neural Information Processing Systems (NeurIPS), 2022

• Learning Options via Compression
  Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn
  In Neural Information Processing Systems (NeurIPS), 2022

• Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation
  Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh
  In Neural Information Processing Systems (NeurIPS), 2022

• Communicating via Markov Decision Processes
  Samuel Sokota, Christian A Schroeder De Witt, Maximilian Igl, Luisa M Zintgraf, Philip Torr, Martin Strohmeier, Zico Kolter, Shimon Whiteson, Jakob Foerster
  In International Conference on Machine Learning (ICML), 2022

• A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks
  Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
  In International Conference on Machine Learning (ICML), 2022

• Deep Equilibrium Optical Flow Estimation
  Shaojie Bai*, Zhengyang Geng*, Yash Savani, J. Zico Kolter
  In Conference on Computer Vision and Pattern Recognition (CVPR), 2022

• Assessing Generalization via Disagreement
  Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2022

• A Fine-Tuning Approach to Belief State Modeling
  Samuel Sokota, Hengyuan Hu, David J Wu, J. Zico Kolter, Jakob Nicolaus Foerster, Noam Brown
  In International Conference on Learning Representations (ICLR), 2022

• Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation
  Colin Wei, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2022

• Neural Deep Equilibrium Solvers
  Shaojie Bai, Vladlen Koltun, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2022

2021

• Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification
  Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
  In Neural Information Processing Systems, (NeurIPS), 2021

• Joint inference and input optimization in equilibrium networks
  Swaminathan Gurumurthy, Shaojie Bai, Zachary Manchester, J. Zico Kolter
  In Neural Information Processing Systems, (NeurIPS), 2021

• Adversarially robust learning for security-constrained optimal power flow
  Priya L. Donti, Aayushya Agarwal, Neeraj Vijay Bedmutha, Larry Pileggi, J. Zico Kolter In Neural Information Processing Systems, (NeurIPS), 2021

• (Implicit)²: Implicit Layers for Implicit Representations
  Zhichun Huang, Shaojie Bai, J. Zico Kolter
  In Neural Information Processing Systems, (NeurIPS), 2021

• Robustness between the worst and average case
  Leslie Rice, Anna Bair, Huan Zhang, J. Zico Kolter
  In Neural Information Processing Systems, (NeurIPS), 2021

• Monte Carlo Tree Search With Iteratively Refining State Abstractions
  Samuel Sokota, Caleb Ho, Zaheen Farraz Ahmad, J. Zico Kolter
  In Neural Information Processing Systems, (NeurIPS), 2021

• Boosted CVaR Classification
  Runtian Zhai, Chen Dan, Arun Suggala, J. Zico Kolter, Pradeep Kumar Ravikumar
  In Neural Information Processing Systems, (NeurIPS), 2021

• Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds
  Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar
  In Neural Information Processing Systems, (NeurIPS), 2021

• Stabilizing Equilibrium Models by Jacobian Regularization
  Shaojie Bai, Vladlen Koltun, J. Zico Kolter
  In Interntional Conference on Machine Learning (ICML), 2021

• On Proximal Policy Optimization’s Heavy-tailed Gradients
  Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar
  In Interntional Conference on Machine Learning (ICML), 2021

• DORO: Distributional and Outlier Robust Optimization
  Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Ravikumar
  In Interntional Conference on Machine Learning (ICML), 2021

• RATT: Leveraging Unlabeled Data to Guarantee Generalization
  Saurabh Garg, Sivaraman Balakrishnan, J. Zico Kolter, Zachary C. Lipton
  In Interntional Conference on Machine Learning (ICML), 2021

• Defending Multimodal Fusion Models Against Single-Source Adversaries
  Karren Yang, Wan-Yi Lin, Manash Barman, Filipe Condessa, J. Zico Kolter
  In Conference on Computer Vision and Pattern Recognition (CVPR), 2021

• Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes
  Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter
  In Conference on Knowledge Discovery and Data Mining (KDD), 2021

• A Bayesian Model of Cash Bail Decisions
  Joshua Williams, J. Zico Kolter
  In ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021

• DC3: A learning method for optimization with hard constraints
  Priya L. Donti, David Rolnick, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

• Orthogonalizing Convolutional Layers with the Cayley Transform
  Asher Trockman, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

• Enforcing robust control guarantees within neural network policies
  Priya L. Donti, Melrose Roderick, Mahyar Fazlyab, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

• Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
  Jeremy M. Cohen, Simran Kaur, Yuanzhi Li, J. Zico Kolter, Ameet Talwalkar
  In International Conference on Learning Representations (ICLR), 2021

• Multiplicative Filter Networks
  Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

• Provably robust classification of adversarial examples with detection
  Fatemeh Sheikholeslami, Ali Lotfi, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

• Estimating Lipschitz constants of monotone deep equilibrium models
  Chirag Pabbaraju, Ezra Winston, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

• Learning perturbation sets for robust machine learning
  Eric Wong, J. Zico Kolter
  In International Conference on Learning Representations (ICLR), 2021

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 low-cardinality semidefinite programming
  Po-Wei Wang, J. Zico Kolter
  In Neural Information Processing Systems, 2020

• Efficient semidefinite-programming-based inference for binary and multi-class MRFs
  Chirag Pabbaraju, Po-Wei 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 Belbute-Peres, 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 Label-Flipping Attacks via Randomized Smoothing
  Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, J. Zico Kolter
  In International Conference on Machine Learning, 2020

• AP-Perf: 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
  Po-Wei 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 f-Divergences
  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 Wake-word 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
  Po-Wei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter
  In International Conference on Machine Learning, 2019

• Adversarial camera stickers: A physical camera-based 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 PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
  Vaishnavh Nagarajan, J. Zico Kolter
  In International Conference on Learning Representations, 2019

• A continuous-time 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 two-player zero-sum games
  Chun Kai Ling, Fei Fang, J. Zico Kolter
  In AAAI, 2019

• Low-rank semidefinite programming for the MAX2SAT problem
  Po-Wei Wang, J. Zico Kolter
  In AAAI, 2019

2018

• End-to-end differentiable physics for learning and control
  Filipe de A. Belbute-Peres, 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 end-to-end 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 low-rank semidefinite programming
  Po-Wei Wang, Wei-Cheng 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? End-to-end 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

• Task-based End-to-end 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
  Po-Wei Wang, Chun-Liang 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 lid-driven cavity
  Rohit Deshmukh, Jack J. McNamara, Zongxian Liang, J. Zico Kolter, Abhijit Gogulapati
  In Journal of Fluid Mechanics (2016), Vol 808, pp. 189–223.

• Epigraph projections for fast general convex programming
  Po-wei 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, Po-wei 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

• Large-scale 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 Off-Policy 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 Large-Scale 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

• Camera-based 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 Open-loop and Closed-loop 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

• Near-Bayesian 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 Least-Squares Temporal Difference Learning
  J. Zico Kolter, Andrew Y. Ng
  In Proceedings of the International Conference on Machine Learning, 2009

• Task-Space 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

• Space-indexed 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