James Harrison

发表

General-Purpose In-Context Learning by Meta-Learning Transformers

Luke Metz, Louis Kirsch, Jascha Narain Sohl-Dickstein, 2022, ArXiv.

VeLO: Training Versatile Learned Optimizers by Scaling Up

Ben Poole, Igor Mordatch, James Bradbury, 2022, ArXiv.

A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases

Luke Metz, J. Harrison, Jascha Narain Sohl-Dickstein, 2022, NeurIPS.

Continuous Meta-Learning without Tasks pdf

Marco Pavone, Chelsea Finn, Apoorva Sharma, 2019, NeurIPS.

Safe Active Dynamics Learning and Control: A Sequential Exploration–Exploitation Framework

M. Pavone, Apoorva Sharma, T. Lew, 2020, IEEE Transactions on Robotics.

Meta-Learning Priors for Efficient Online Bayesian Regression

Marco Pavone, Apoorva Sharma, James Harrison, 2018, WAFR.

Bayesian Embeddings for Few-Shot Open World Recognition

Steven L. Waslander, Chelsea Finn, M. Pavone, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Learning Sampling Distributions for Robot Motion Planning

Marco Pavone, Brian Ichter, James Harrison, 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).

Network offloading policies for cloud robotics: a learning-based approach pdf

Marco Pavone, Apoorva Sharma, Sandeep Chinchali, 2019, Autonomous Robots.

Coherence Time ! = # ! = $ Query Cloud SVM Classifier Robot Model FaceNet Embed

Daniel Kang, M. Pavone, J. Harrison, 2022 .

BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning

Mo Chen, Marco Pavone, Apoorva Sharma, 2018, 2019 International Conference on Robotics and Automation (ICRA).

ADAPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems pdf

Silvio Savarese, Marco Pavone, Yuke Zhu, 2017, ISRR.

Deep Reinforcement Learning amidst Lifelong Non-Stationarity pdf

Chelsea Finn, Annie Xie, James Harrison, 2020, ArXiv.

Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems

M. Pavone, J. Harrison, Maximilian Schiffer, 2022, ArXiv.

Practical tradeoffs between memory, compute, and performance in learned optimizers

Luke Metz, Niru Maheswaranathan, J. Harrison, 2022, CoLLAs.

Adaptive Robust Model Predictive Control via Uncertainty Cancellation

Spencer M. Richards, M. Pavone, J. Harrison, 2022, ArXiv.

Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty

Spencer M. Richards, M. Pavone, Rohan Sinha, 2021, 2022 American Control Conference (ACC).

Adaptive Meta-Learning for Identification of Rover-Terrain Dynamics pdf

J. Harrison, M. Pavone, S. Banerjee, 2020, ArXiv.

Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning

M. Pavone, B. Ivanovic, James Harrison, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Robust and Adaptive Planning under Model Uncertainty pdf

Marco Pavone, Apoorva Sharma, Matthew Tsao, 2019, ICAPS.

Particle MPC for Uncertain and Learning-Based Control

Marco Pavone, Apoorva Sharma, James Harrison, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems pdf

Marco Pavone, Kaidi Yang, Daniele Gammelli, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

Noise-Reuse in Online Evolution Strategies

Virginia Smith, Luke Metz, Oscar Li, 2023, ArXiv.

Graph Reinforcement Learning for Network Control via Bi-Level Optimization

M. Pavone, Francisco Pereira, Kaidi Yang, 2023, ICML.

Control Adaptation via Meta-Learning Dynamics

R. Calandra, M. Pavone, J. Harrison, 2018 .

Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems

M. Pavone, Maximilian Schiffer, James Harrison, 2022, L4DC.

Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies

Virginia Smith, Luke Metz, Oscar Li, 2023, NeurIPS.

Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand

M. Pavone, Kaidi Yang, Filipe Rodrigues, 2022, KDD.

On the Problem of Reformulating Systems with Uncertain Dynamics as a Stochastic Differential Equation pdf

Thomas Lew, Marco Pavone, Edward Schmerling, 2021, ArXiv.

Safe Model-Based Meta-Reinforcement Learning: A Sequential Exploration-Exploitation Framework pdf

Thomas Lew, Marco Pavone, Apoorva Sharma, 2020, ArXiv.

Safe Sequential Exploration and Exploitation

M. Pavone, J. Harrison, Apoorva Sharma, 2020 .

Safe Learning and Control using Meta-Learning

Thomas Lew, Marco Pavone, Apoorva Sharma, 2010 .