2022
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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