Jeremy Z. Kolter
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Jeremy Z. Koltercomputer-science Degrees
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Computer Science
Jeremy Z. Kolter's Degrees
- Bachelors Computer Science Carnegie Mellon University
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Why Is Jeremy Z. Kolter Influential?
(Suggest an Edit or Addition)Jeremy Z. Kolter's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling (2018) (2561)
- Provable defenses against adversarial examples via the convex outer adversarial polytope (2017) (1244)
- Certified Adversarial Robustness via Randomized Smoothing (2019) (1239)
- REDD : A Public Data Set for Energy Disaggregation Research (2011) (1134)
- Towards fully autonomous driving: Systems and algorithms (2011) (1064)
- Fast is better than free: Revisiting adversarial training (2020) (705)
- Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts (2007) (690)
- Learning to Detect and Classify Malicious Executables in the Wild (2006) (608)
- OptNet: Differentiable Optimization as a Layer in Neural Networks (2017) (602)
- Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation (2012) (598)
- Learning to detect malicious executables in the wild (2004) (499)
- Multimodal Transformer for Unaligned Multimodal Language Sequences (2019) (490)
- Dynamic weighted majority: a new ensemble method for tracking concept drift (2003) (439)
- Overfitting in adversarially robust deep learning (2020) (430)
- Scaling provable adversarial defenses (2018) (395)
- Deep Equilibrium Models (2019) (379)
- Energy Disaggregation via Discriminative Sparse Coding (2010) (350)
- Differentiable Convex Optimization Layers (2019) (333)
- Gradient descent GAN optimization is locally stable (2017) (310)
- Input Convex Neural Networks (2016) (304)
- End-to-End Differentiable Physics for Learning and Control (2018) (293)
- Using additive expert ensembles to cope with concept drift (2005) (273)
- Near-Bayesian exploration in polynomial time (2009) (269)
- Differentiable MPC for End-to-end Planning and Control (2018) (244)
- Regularization and feature selection in least-squares temporal difference learning (2009) (221)
- Uniform convergence may be unable to explain generalization in deep learning (2019) (206)
- Task-based End-to-end Model Learning in Stochastic Optimization (2017) (206)
- A control architecture for quadruped locomotion over rough terrain (2008) (195)
- SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver (2019) (167)
- Wasserstein Adversarial Examples via Projected Sinkhorn Iterations (2019) (161)
- Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion (2007) (157)
- Patches Are All You Need? (2022) (135)
- A Large-Scale Study on Predicting and Contextualizing Building Energy Usage (2011) (132)
- Multiscale Deep Equilibrium Models (2020) (117)
- Learning Stable Deep Dynamics Models (2020) (113)
- Trellis Networks for Sequence Modeling (2018) (107)
- Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction (2020) (106)
- On Physical Adversarial Patches for Object Detection (2019) (103)
- Adversarial camera stickers: A physical camera-based attack on deep learning systems (2019) (101)
- Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting (2013) (100)
- Adversarial Robustness Against the Union of Multiple Perturbation Models (2019) (98)
- The Stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion (2011) (95)
- Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability (2021) (90)
- Demand Response of Ancillary Service From Industrial Loads Coordinated With Energy Storage (2018) (89)
- Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience (2019) (87)
- Certified Robustness to Label-Flipping Attacks via Randomized Smoothing (2020) (80)
- What game are we playing? End-to-end learning in normal and extensive form games (2018) (75)
- A multiple quantile regression approach to the wind, solar, and price tracks of GEFCom2014 (2016) (74)
- A Continuous-Time View of Early Stopping for Least Squares Regression (2018) (72)
- Generalization in Deep Networks: The Role of Distance from Initialization (2019) (71)
- Monotone operator equilibrium networks (2020) (69)
- Policy search via the signed derivative (2009) (68)
- A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving (2010) (68)
- Contextually Supervised Source Separation with Application to Energy Disaggregation (2013) (66)
- Stereo vision and terrain modeling for quadruped robots (2009) (66)
- Denoised Smoothing: A Provable Defense for Pretrained Classifiers (2020) (66)
- Learning perturbation sets for robust machine learning (2020) (64)
- Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Verification (2021) (58)
- DC3: A learning method for optimization with hard constraints (2021) (57)
- Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification (2021) (55)
- Task-space trajectories via cubic spline optimization (2009) (55)
- Orthogonalizing Convolutional Layers with the Cayley Transform (2021) (53)
- A Framework for robustness Certification of Smoothed Classifiers using F-Divergences (2020) (52)
- The Fixed Points of Off-Policy TD (2011) (50)
- Convolutional Sequence Modeling Revisited (2018) (50)
- Enforcing robust control guarantees within neural network policies (2020) (41)
- Adversarial Music: Real World Audio Adversary Against Wake-word Detection System (2019) (41)
- Large-scale probabilistic forecasting in energy systems using sparse Gaussian conditional random fields (2013) (40)
- Assessing Generalization of SGD via Disagreement (2021) (39)
- Optimal Planning and Learning in Uncertain Environments for the Management of Wind Farms (2015) (35)
- Intelligent Pothole Detection and Road Condition Assessment (2017) (32)
- Stabilizing Equilibrium Models by Jacobian Regularization (2021) (31)
- Learning omnidirectional path following using dimensionality reduction (2007) (30)
- Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (2021) (28)
- A moving horizon state estimator in the control of thermostatically controlled loads for demand response (2013) (25)
- Black-box Adversarial Attacks with Bayesian Optimization (2019) (25)
- Model predictive control of industrial loads and energy storage for demand response (2016) (24)
- A Semismooth Newton Method for Fast, Generic Convex Programming (2017) (24)
- Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization (2021) (24)
- DORO: Distributional and Outlier Robust Optimization (2021) (24)
- Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games (2019) (24)
- Machine Learning for Sustainable Energy Systems (2021) (24)
- The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints (2017) (23)
- The Limited Multi-Label Projection Layer (2019) (22)
- Differentiable learning of numerical rules in knowledge graphs (2020) (22)
- Perceptual Based Adversarial Audio Attacks (2019) (21)
- Task-based End-to-end Model Learning (2017) (21)
- Space-indexed dynamic programming: learning to follow trajectories (2008) (21)
- Dojo: A Differentiable Simulator for Robotics (2022) (20)
- The Multiple Quantile Graphical Model (2016) (20)
- Realtime Query Completion via Deep Language Models (2018) (19)
- Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control (2016) (19)
- A Fast Algorithm for Sparse Controller Design (2013) (19)
- Estimating Lipschitz constants of monotone deep equilibrium models (2021) (18)
- Black-box Smoothing: A Provable Defense for Pretrained Classifiers (2020) (18)
- Fast Newton methods for the group fused lasso (2014) (18)
- Poisoned classifiers are not only backdoored, they are fundamentally broken (2020) (17)
- RATT: Leveraging Unlabeled Data to Guarantee Generalization (2021) (16)
- Learning to Detect Malicious Executables (2006) (16)
- Model order reduction using sparse coding exemplified for the lid-driven cavity (2016) (15)
- Deep Equilibrium Optical Flow Estimation (2022) (15)
- The Mixing method: coordinate descent for low-rank semidefinite programming (2017) (15)
- Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes (2020) (15)
- (Certified!!) Adversarial Robustness for Free! (2022) (15)
- Provably robust classification of adversarial examples with detection (2021) (14)
- AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning (2019) (14)
- General Cutting Planes for Bound-Propagation-Based Neural Network Verification (2022) (13)
- Design, analysis, and learning control of a fully actuated micro wind turbine (2012) (13)
- A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games (2022) (12)
- Deep Archimedean Copulas (2020) (12)
- Adversarial camera stickers: A Physical Camera Attack on Deep Learning Classifier (2019) (10)
- Low-rank semidefinite programming for the MAX2SAT problem (2018) (10)
- How Much Are We Saving after All? Characterizing the Effects of Commonly Varying Assumptions on Emissions and Damage Estimates in PJM. (2019) (10)
- Learning and control with inaccurate models (2010) (10)
- Dynamic Modeling and Equilibria in Fair Decision Making (2019) (9)
- Understanding Why Generalized Reweighting Does Not Improve Over ERM (2022) (9)
- Challenging common interpretability assumptions in feature attribution explanations (2020) (9)
- A community-powered search of machine learning strategy space to find NMR property prediction models (2020) (9)
- Epigraph projections for fast general convex programming (2016) (9)
- Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation (2022) (9)
- Defending Multimodal Fusion Models against Single-Source Adversaries (2021) (9)
- Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization (2015) (8)
- Convex programming with fast proximal and linear operators (2015) (8)
- Boosted CVaR Classification (2021) (7)
- Computational approaches for efficient scheduling of steel plants as demand response resource (2016) (7)
- Joint inference and input optimization in equilibrium networks (2021) (7)
- Robustness between the worst and average case (2021) (7)
- On Proximal Policy Optimization's Heavy-tailed Gradients (2021) (6)
- DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting (2021) (6)
- Neural Variational Identification and Filtering for Stochastic Non-linear Dynamical Systems with Application to Non-intrusive Load Monitoring (2019) (6)
- Neural Network Virtual Sensors for Fuel Injection Quantities with Provable Performance Specifications (2020) (6)
- A Fine-Tuning Approach to Belief State Modeling (2022) (5)
- Dojo: A Differentiable Physics Engine for Robotics (2022) (5)
- Provably Safe PAC-MDP Exploration Using Analogies (2020) (5)
- Input-Convex Deep Networks (2016) (5)
- Monte Carlo Tree Search With Iteratively Refining State Abstractions (2021) (4)
- Communicating via Markov Decision Processes (2021) (4)
- An Additive Autoregressive Hidden Markov Model for Energy Disaggregation (2015) (3)
- Efficient semidefinite-programming-based inference for binary and multi-class MRFs (2020) (3)
- Polynomial Optimization Methods for Matrix Factorization (2017) (3)
- Probabilistic Learning and Planning for Optimal Management of Wind Farms (2013) (2)
- Perfectly Secure Steganography Using Minimum Entropy Coupling (2022) (2)
- Energy balance of reduced order models for unsteady flows using sparse coding (2018) (2)
- Characterizing Datapoints via Second-Split Forgetting (2022) (2)
- Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification (2021) (2)
- An SVD and Derivative Kernel Approach to Learning from Geometric Data (2015) (1)
- A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks (2022) (1)
- Abstracting Imperfect Information Away from Two-Player Zero-Sum Games (2023) (1)
- Empirical robustification of pre-trained classifiers (2021) (1)
- Community detection using fast low-cardinality semidefinite programming (2020) (1)
- Provably robust deep generative models (2020) (1)
- Expedient and Parallelizable Sparse Coding Algorithm for Large Datasets (2016) (1)
- Losses over Labels: Weakly Supervised Learning via Direct Loss Construction (2022) (1)
- Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks (2019) (1)
- Epigraph proximal algorithms for general convex programming (2015) (0)
- AT THE E DGE OF S TABILITY (2021) (0)
- Employing adversarial robustness techniques for large-scale stochastic optimal power flow (2022) (0)
- Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth (2022) (0)
- A Bayesian Model of Cash Bail Decisions (2021) (0)
- Hierarchical Modeling of S ystems with Similar Components (2015) (0)
- Hierachical modeling of systems with similar components (2015) (0)
- Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport (2023) (0)
- Understanding the Covariance Structure of Convolutional Filters (2022) (0)
- The Pitfalls of Regularization in Off-Policy TD Learning (2022) (0)
- Permutation Equivariant Neural Functionals (2023) (0)
- Orbital Mixer: Using Atomic Orbital Features for Basis-Dependent Prediction of Molecular Wavefunctions. (2022) (0)
- Probabilistic Segmentation via Total Variation Regularization (2015) (0)
- The Update Equivalence Framework for Decision-Time Planning (2023) (0)
- Adversarially Robust Learning for Security-Constrained Optimal Power Flow (2021) (0)
- Design , Analysis , and Learning Control of a Robotic Wind Turbine (2011) (0)
- Learning with Explanation Constraints (2023) (0)
- C ERTIFIED R OBUSTNESS FOR D EEP E QUILIBRIUM M ODELS VIA I NTERVAL B OUND P ROPAGATION (2022) (0)
- Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games (2022) (0)
- The Effect of Pre-ReLU Input Distribution on DNN’s Performance (2017) (0)
- Smooth-Reduce: Leveraging Patches for Improved Certified Robustness (2022) (0)
- Adaptive Decision Making Using Probabilistic Programming and Stochastic Optimization (2018) (0)
- Energy balance of reduced order models for unsteady flows using sparse coding (2018) (0)
- Model-tuning Via Prompts Makes NLP Models Adversarially Robust (2023) (0)
- DORO: Distributional and Outlier Robust Optimization (Appendix) (2021) (0)
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