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ORCIDMatt Barnes 0001
Person information
- affiliation: Google
- affiliation (Ph.D.): Carnegie Mellon University, PA, USA
Other persons with the same name
- Matt Barnes 0002 — University of California, USA
- Matthew Barnes — disambiguation page
2020 – today
- 2024
[c10]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- [c9]Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jorg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller:
Imitating Language via Scalable Inverse Reinforcement Learning. NeurIPS 2024 - [i11]Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jorg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Maria Elisabeth Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller:
Imitating Language via Scalable Inverse Reinforcement Learning. CoRR abs/2409.01369 (2024) - 2023
- [i10]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 abs/2305.11290 (2023) - 2022
- [j1]Jonathan C. Spencer, Sanjiban Choudhury, Matthew Barnes, Matthew Schmittle, Mung Chiang, Peter J. Ramadge, Siddhartha S. Srinivasa:
Expert Intervention Learning. Auton. Robots 46(1): 99-113 (2022) - [i9]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 abs/2202.01934 (2022) - 2021
- [c8]Liyiming Ke, Sanjiban Choudhury, Matt Barnes, Wen Sun, Gilwoo Lee, Siddhartha S. Srinivasa:
Imitation Learning as f-Divergence Minimization. WAFR 2021: 313-329 - 2020
- [c7]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: 9659-9666 - [c6]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 - [i8]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 abs/2007.03113 (2020)
2010 – 2019
- 2019
- [c5]Matt Barnes, Artur Dubrawski:
On the Interaction Effects Between Prediction and Clustering. AISTATS 2019: 118-126 - [c4]Samuel K. Ainsworth, Matt Barnes, Siddhartha S. Srinivasa:
Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation. NeurIPS 2019: 15156-15166 - [i7]Liyiming Ke, Matt Barnes, Wen Sun, Gilwoo Lee, Sanjiban Choudhury, Siddhartha S. Srinivasa:
Imitation Learning as f-Divergence Minimization. CoRR abs/1905.12888 (2019) - [i6]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 abs/1908.07088 (2019) - [i5]Samuel K. Ainsworth, Matt Barnes, Siddhartha S. Srinivasa:
Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation. CoRR abs/1912.01649 (2019) - 2018
- [i4]Matt Barnes, Artur Dubrawski:
Dependency Leakage: Analysis and Scalable Estimators. CoRR abs/1807.06713 (2018) - 2017
- [c3]Rebecca C. Steorts, Matt Barnes, Willie Neiswanger:
Performance Bounds for Graphical Record Linkage. AISTATS 2017: 298-306 - [c2]Matt Barnes, Artur Dubrawski:
The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters. UAI 2017 - [i3]Rebecca C. Steorts, Matt Barnes, Willie Neiswanger:
Performance Bounds for Graphical Record Linkage. CoRR abs/1703.02679 (2017) - 2015
- [c1]Matt Barnes, Nick Gisolfi, Madalina Fiterau, Artur Dubrawski:
Leveraging Common Structure to Improve Prediction across Related Datasets. AAAI 2015: 4144-4145 - [i2]Matt Barnes, Kyle Miller, Artur Dubrawski:
Performance Bounds for Pairwise Entity Resolution. CoRR abs/1509.03302 (2015) - [i1]Matt Barnes:
A Practioner's Guide to Evaluating Entity Resolution Results. CoRR abs/1509.04238 (2015)
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