Matt Barnes

According to our database, Matt Barnes authored at least 16 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Massively Scalable Inverse Reinforcement Learning in Google Maps.

Matt Barnes, Matthew Abueg, Oliver F. Lange, Matt Deeds, Jason Trader, Denali Molitor, Markus Wulfmeier, Shawn O'Banion

CoRR, 2023

2022

Smartphone-based Hard-braking Event Detection at Scale for Road Safety Services.

Luyang Liu, David Racz, Kara Vaillancourt, Julie Michelman, Matt Barnes, Stefan Mellem, Paul Eastham, Bradley Green, Charles Armstrong, Rishi Bal, Shawn O'Banion, Feng Guo

CoRR, 2022

Expert Intervention Learning.

Jonathan C. Spencer, Sanjiban Choudhury, Matthew Barnes, Matthew Schmittle, Mung Chiang, Peter J. Ramadge, Siddhartha S. Srinivasa

Auton. Robots, 2022

2021

Imitation Learning as f-Divergence Minimization.

Liyiming Ke, Sanjiban Choudhury, Matt Barnes, Wen Sun, Gilwoo Lee, Siddhartha S. Srinivasa

Proceedings of the Algorithmic Foundations of Robotics XIV, 2021

2020

Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks.

Amol Kapoor, Xue Ben, Luyang Liu, Bryan Perozzi, Matt Barnes, Martin Blais, Shawn O'Banion

CoRR, 2020

Learning from Interventions: Human-robot interaction as both explicit and implicit feedback.

Jonathan C. Spencer, Sanjiban Choudhury, Matt Barnes, Matthew Schmittle, Mung Chiang, Peter J. Ramadge, Siddhartha S. Srinivasa

Proceedings of the Robotics: Science and Systems XVI, 2020

Adaptive Robot-Assisted Feeding: An Online Learning Framework for Acquiring Previously Unseen Food Items.

Ethan K. Gordon, Xiang Meng, Tapomayukh Bhattacharjee, Matt Barnes, Siddhartha S. Srinivasa

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2019

Learning from failures in robot-assisted feeding: Using online learning to develop manipulation strategies for bite acquisition.

Ethan K. Gordon, Xiang Meng, Matt Barnes, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa

CoRR, 2019

Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation.

Samuel K. Ainsworth, Matt Barnes, Siddhartha S. Srinivasa

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Interaction Effects Between Prediction and Clustering.

Matt Barnes, Artur Dubrawski

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Dependency Leakage: Analysis and Scalable Estimators.

Matt Barnes, Artur Dubrawski

CoRR, 2018

2017

The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters.

Matt Barnes, Artur Dubrawski

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Performance Bounds for Graphical Record Linkage.

Rebecca C. Steorts, Matt Barnes, Willie Neiswanger

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2015

Performance Bounds for Pairwise Entity Resolution.

Matt Barnes, Kyle Miller, Artur Dubrawski

CoRR, 2015

A Practioner's Guide to Evaluating Entity Resolution Results.

Matt Barnes

CoRR, 2015

Leveraging Common Structure to Improve Prediction across Related Datasets.

Matt Barnes, Nick Gisolfi, Madalina Fiterau, Artur Dubrawski

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015