Matt Barnes

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 16

Top Topics

Entity Resolution

Top Venues

Publications

Matt Barnes, Matthew Abueg, Oliver F. Lange, Matt Deeds, Jason Trader, Denali Molitor, Markus Wulfmeier, Shawn O'Banion
Massively Scalable Inverse Reinforcement Learning in Google Maps. ICLR (2024)
Matt Barnes, Matthew Abueg, Oliver F. Lange, Matt Deeds, Jason Trader, Denali Molitor, Markus Wulfmeier, Shawn O'Banion
Massively Scalable Inverse Reinforcement Learning in Google Maps. CoRR (2023)
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
Smartphone-based Hard-braking Event Detection at Scale for Road Safety Services. CoRR (2022)
Liyiming Ke, Sanjiban Choudhury, Matt Barnes, Wen Sun, Gilwoo Lee, Siddhartha S. Srinivasa
Imitation Learning as f-Divergence Minimization. WAFR (2021)
Amol Kapoor, Xue Ben, Luyang Liu, Bryan Perozzi, Matt Barnes, Martin Blais, Shawn O'Banion
Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks. CoRR (2020)
Jonathan C. Spencer, Sanjiban Choudhury, Matt Barnes, Matthew Schmittle, Mung Chiang, Peter J. Ramadge, Siddhartha S. Srinivasa
Learning from Interventions: Human-robot interaction as both explicit and implicit feedback. Robotics: Science and Systems (2020)
Ethan K. Gordon, Xiang Meng, Tapomayukh Bhattacharjee, Matt Barnes, Siddhartha S. Srinivasa
Adaptive Robot-Assisted Feeding: An Online Learning Framework for Acquiring Previously Unseen Food Items. IROS (2020)
Matt Barnes, Artur Dubrawski
On the Interaction Effects Between Prediction and Clustering. AISTATS (2019)
Ethan K. Gordon, Xiang Meng, Matt Barnes, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa
Learning from failures in robot-assisted feeding: Using online learning to develop manipulation strategies for bite acquisition. CoRR (2019)
Samuel K. Ainsworth, Matt Barnes, Siddhartha S. Srinivasa
Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation. NeurIPS (2019)
Liyiming Ke, Matt Barnes, Wen Sun, Gilwoo Lee, Sanjiban Choudhury, Siddhartha S. Srinivasa
Imitation Learning as f-Divergence Minimization. CoRR (2019)
Samuel K. Ainsworth, Matt Barnes, Siddhartha S. Srinivasa
Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation. CoRR (2019)
Matt Barnes, Artur Dubrawski
Dependency Leakage: Analysis and Scalable Estimators. CoRR (2018)
Rebecca C. Steorts, Matt Barnes, Willie Neiswanger
Performance Bounds for Graphical Record Linkage. CoRR (2017)
Matt Barnes, Artur Dubrawski
The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters. UAI (2017)
Rebecca C. Steorts, Matt Barnes, Willie Neiswanger
Performance Bounds for Graphical Record Linkage. AISTATS (2017)
Matt Barnes, Nick Gisolfi, Madalina Fiterau, Artur Dubrawski
Leveraging Common Structure to Improve Prediction across Related Datasets. AAAI (2015)
Matt Barnes
A Practioner's Guide to Evaluating Entity Resolution Results. CoRR (2015)
Matt Barnes, Kyle Miller, Artur Dubrawski
Performance Bounds for Pairwise Entity Resolution. CoRR (2015)