Leveraging Common Structure to Improve Prediction across Related Datasets. - Matt Barnes 001; Nick Gisolfi; Madalina Fiterau; Artur Dubrawski (AAAI, 2015)

A Practioner's Guide to Evaluating Entity Resolution Results. - Matt Barnes 001 (CoRR, 2015)

Performance Bounds for Pairwise Entity Resolution. - Matt Barnes 001; Kyle Miller 001; Artur Dubrawski (CoRR, 2015)

Performance Bounds for Graphical Record Linkage. - Rebecca C. Steorts; Matt Barnes 001; Willie Neiswanger (AISTATS, 2017)

The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters. - Matt Barnes 001; Artur Dubrawski (UAI, 2017)

Dependency Leakage: Analysis and Scalable Estimators. - Matt Barnes 001; Artur Dubrawski (CoRR, 2018)

On the Interaction Effects Between Prediction and Clustering. - Matt Barnes 001; Artur Dubrawski (AISTATS, 2019)

Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation. - Samuel K. Ainsworth; Matt Barnes 001; Siddhartha S. Srinivasa (NeurIPS, 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 001; Tapomayukh Bhattacharjee; Siddhartha S. Srinivasa (CoRR, 2019)

Adaptive Robot-Assisted Feeding: An Online Learning Framework for Acquiring Previously Unseen Food Items. - Ethan K. Gordon; Xiang Meng; Tapomayukh Bhattacharjee; Matt Barnes 001; Siddhartha S. Srinivasa (IROS, 2020)

Learning from Interventions: Human-robot interaction as both explicit and implicit feedback. - Jonathan C. Spencer; Sanjiban Choudhury; Matt Barnes 001; Matthew Schmittle; Mung Chiang; Peter J. Ramadge; Siddhartha S. Srinivasa (Robotics: Science and Systems, 2020)

Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks. - Amol Kapoor; Xue Ben; Luyang Liu; Bryan Perozzi; Matt Barnes 001; Martin Blais; Shawn O'Banion (CoRR, 2020)

Imitation Learning as f-Divergence Minimization. - Liyiming Ke; Sanjiban Choudhury; Matt Barnes 001; Wen Sun 002; Gilwoo Lee; Siddhartha S. Srinivasa (WAFR, 2021)

Expert Intervention Learning. - Jonathan C. Spencer; Sanjiban Choudhury; Matthew Barnes 001; Matthew Schmittle; Mung Chiang; Peter J. Ramadge; Siddhartha S. Srinivasa (Auton. Robots, 2022)

Smartphone-based Hard-braking Event Detection at Scale for Road Safety Services. - Luyang Liu; David Racz; Kara Vaillancourt; Julie Michelman; Matt Barnes 001; Stefan Mellem; Paul Eastham; Bradley Green; Charles Armstrong; Rishi Bal; Shawn O'Banion; Feng Guo (CoRR, 2022)

Massively Scalable Inverse Reinforcement Learning in Google Maps. - Matt Barnes 001; Matthew Abueg; Oliver F. Lange; Matt Deeds; Jason Trader; Denali Molitor; Markus Wulfmeier; Shawn O'Banion (ICLR, 2024)

Imitating Language via Scalable Inverse Reinforcement Learning. - Markus Wulfmeier; Michael Bloesch; Nino Vieillard; Arun Ahuja; Jörg Bornschein; Sandy H. Huang; Artem Sokolov; Matt Barnes 001; Guillaume Desjardins; Alex Bewley; Sarah Bechtle; Jost Tobias Springenberg; et al. (NeurIPS, 2024)