James Harrison

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 55

Top Topics

Predictive Control

Dynamical Systems

Reinforcement Learning

Top Venues

Publications

Tobias Enders, James Harrison, Maximilian Schiffer
Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution Shifts. CoRR (2024)
John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven L. Waslander
Bayesian Embeddings for Few-Shot Open World Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 46 (3) (2024)
Siddharth Nayak, Adelmo Morrison Orozco, Marina Ten Have, Vittal Thirumalai, Jackson Zhang, Darren Chen, Aditya Kapoor, Eric Robinson, Karthik Gopalakrishnan, James Harrison, Brian Ichter, Anuj Mahajan, Hamsa Balakrishnan
Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments. CoRR (2024)
Allan Zhou, Chelsea Finn, James Harrison
Universal Neural Functionals. CoRR (2024)
James Harrison, John Willes, Jasper Snoek
Variational Bayesian Last Layers. ICLR (2024)
James Harrison, John Willes, Jasper Snoek
Variational Bayesian Last Layers. CoRR (2024)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T. Parisi, Abhishek Kumar, Alexander A. Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. ICML (2023)
Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems. L4DC (2023)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR (2023)
Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. CoRR (2023)
Oscar Li, James Harrison, Jascha Sohl-Dickstein, Virginia Smith, Luke Metz
Noise-Reuse in Online Evolution Strategies. CoRR (2023)
Oscar Li, James Harrison, Jascha Sohl-Dickstein, Virginia Smith, Luke Metz
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies. NeurIPS (2023)
Boris Ivanovic, James Harrison, Marco Pavone
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning. ICRA (2023)
James Blundell, Charlotte Collins, Rod Sears, Tassos Plioutsias, John Huddlestone, Don Harris, James Harrison, Anthony Kershaw, Paul Harrison, Phil Lamb
Multivariate Analysis of Gaze Behavior and Task Performance Within Interface Design Evaluation. IEEE Trans. Hum. Mach. Syst. 53 (5) (2023)
Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein
Practical tradeoffs between memory, compute, and performance in learned optimizers. CoRR (2022)
Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein
Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers. CoLLAs (2022)
Louis Kirsch, James Harrison, Jascha Sohl-Dickstein, Luke Metz
General-Purpose In-Context Learning by Meta-Learning Transformers. CoRR (2022)
Boris Ivanovic, James Harrison, Marco Pavone
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning. CoRR (2022)
Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. KDD (2022)
Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein
VeLO: Training Versatile Learned Optimizers by Scaling Up. CoRR (2022)
Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. CoRR (2022)
Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems. CoRR (2022)
Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty. ACC (2022)
James Harrison, Luke Metz, Jascha Sohl-Dickstein
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases. NeurIPS (2022)
Thomas Lew, Apoorva Sharma, James Harrison, Andrew Bylard, Marco Pavone
Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework. IEEE Trans. Robotics 38 (5) (2022)
James Harrison, Luke Metz, Jascha Sohl-Dickstein
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases. CoRR (2022)
Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
Adaptive Robust Model Predictive Control via Uncertainty Cancellation. CoRR (2022)
Robert Dyro, James Harrison, Apoorva Sharma, Marco Pavone
Particle MPC for Uncertain and Learning-Based Control. CoRR (2021)
Annie Xie, James Harrison, Chelsea Finn
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity. ICML (2021)
Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
Network offloading policies for cloud robotics: a learning-based approach. Auton. Robots 45 (7) (2021)
Robert Dyro, James Harrison, Apoorva Sharma, Marco Pavone
Particle MPC for Uncertain and Learning-Based Control. IROS (2021)
Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CoRR (2021)
Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CDC (2021)
John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven Lake Waslander
Bayesian Embeddings for Few-Shot Open World Recognition. CoRR (2021)
Thomas Lew, Apoorva Sharma, James Harrison, Edward Schmerling, Marco Pavone
On the Problem of Reformulating Systems with Uncertain Dynamics as a Stochastic Differential Equation. CoRR (2021)
Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty. CoRR (2021)
Thomas Lew, Apoorva Sharma, James Harrison, Marco Pavone
Safe Model-Based Meta-Reinforcement Learning: A Sequential Exploration-Exploitation Framework. CoRR (2020)
Annie Xie, James Harrison, Chelsea Finn
Deep Reinforcement Learning amidst Lifelong Non-Stationarity. CoRR (2020)
Somrita Banerjee, James Harrison, P. Michael Furlong, Marco Pavone
Adaptive Meta-Learning for Identification of Rover-Terrain Dynamics. CoRR (2020)
James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone
Continuous Meta-Learning without Tasks. NeurIPS (2020)
Boris Ivanovic, James Harrison, Apoorva Sharma, Mo Chen, Marco Pavone
BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning. ICRA (2019)
Apoorva Sharma, James Harrison, Matthew Tsao, Marco Pavone
Robust and Adaptive Planning under Model Uncertainty. CoRR (2019)
Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
Network Offloading Policies for Cloud Robotics: a Learning-based Approach. CoRR (2019)
Apoorva Sharma, James Harrison, Matthew Tsao, Marco Pavone
Robust and Adaptive Planning under Model Uncertainty. ICAPS (2019)
James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone
Continuous Meta-Learning without Tasks. CoRR (2019)
Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
Network Offloading Policies for Cloud Robotics: A Learning-Based Approach. Robotics: Science and Systems (2019)
Boris Ivanovic, James Harrison, Apoorva Sharma, Mo Chen, Marco Pavone
BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning. CoRR (2018)
Brian Ichter, James Harrison, Marco Pavone
Learning Sampling Distributions for Robot Motion Planning. ICRA (2018)
James Harrison, Apoorva Sharma, Marco Pavone
Meta-learning Priors for Efficient Online Bayesian Regression. WAFR (2018)
James Harrison, Apoorva Sharma, Marco Pavone
Meta-Learning Priors for Efficient Online Bayesian Regression. CoRR (2018)
Brian Ichter, James Harrison, Marco Pavone
Learning Sampling Distributions for Robot Motion Planning. CoRR (2017)
James Harrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone
AdaPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems. ISRR (2017)
James Harrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone
ADAPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems. CoRR (2017)
Colin R. Gallacher, James Harrison, József Kövecses
Characterizing device dynamics for haptic manipulation and navigation. ICRA (2015)
Kevin J. Mitchell, Michael J. Becich, Jules J. Berman, Wendy W. Chapman, John R. Gilbertson, Dilip Gupta, James Harrison, Elizabeth Legowski, Rebecca S. Crowley
Implementation and Evaluation of a Negation Tagger in a Pipeline-based System for Information Extraction from Pathology Reports. MedInfo (2004)
Mark Derthick, James Harrison, Andrew Moore, Steven F. Roth
Efficient Multi-Object Dynamic Query Histograms. INFOVIS (1999)