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2020 – today
- 2022
[c10]Sai Kiran Narayanaswami, Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit Narvekar, Peter Stone:
Towards a Real-Time, Low-Resource, End-to-End Object Detection Pipeline for Robot Soccer. RoboCup 2022: 62-74- 2021
- [c9]Keya Ghonasgi, Reuth Mirsky, Sanmit Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, Ashish D. Deshpande:
Capturing Skill State in Curriculum Learning for Human Skill Acquisition. IROS 2021: 771-776 - 2020
- [j2]Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone:
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. J. Mach. Learn. Res. 21: 181:1-181:50 (2020) - [i4]Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone:
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. CoRR abs/2003.04960 (2020)
2010 – 2019
- 2019
- [c8]Sanmit Narvekar, Peter Stone:
Learning Curriculum Policies for Reinforcement Learning. AAMAS 2019: 25-33 - [c7]Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Tushar Chandra, Craig Boutilier:
SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets. IJCAI 2019: 2592-2599 - [i3]Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Morgane Lustman, Vince Gatto, Paul Covington, Jim McFadden, Tushar Chandra, Craig Boutilier:
Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology. CoRR abs/1905.12767 (2019) - [i2]Eugene Ie, Chih-Wei Hsu, Martin Mladenov, Vihan Jain, Sanmit Narvekar, Jing Wang, Rui Wu, Craig Boutilier:
RecSim: A Configurable Simulation Platform for Recommender Systems. CoRR abs/1909.04847 (2019) - 2018
- [i1]Sanmit Narvekar, Peter Stone:
Learning Curriculum Policies for Reinforcement Learning. CoRR abs/1812.00285 (2018) - 2017
- [c6]Sanmit Narvekar, Jivko Sinapov, Peter Stone:
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning. IJCAI 2017: 2536-2542 - [c5]Sanmit Narvekar:
Curriculum Learning in Reinforcement Learning. IJCAI 2017: 5195-5196 - [c4]Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone:
Fast and Precise Black and White Ball Detection for RoboCup Soccer. RoboCup 2017: 45-58 - 2016
- [j1]Katie Genter, Patrick MacAlpine
, Jacob Menashe, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone:
UT Austin Villa: Project-Driven Research in AI and Robotics. IEEE Intell. Syst. 31(2): 94-101 (2016) - [c3]Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, Peter Stone:
Source Task Creation for Curriculum Learning. AAMAS 2016: 566-574 - [c2]Sanmit Narvekar:
Curriculum Learning in Reinforcement Learning: (Doctoral Consortium). AAMAS 2016: 1528-1529 - 2015
- [c1]Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, Peter Stone:
Learning Inter-Task Transferability in the Absence of Target Task Samples. AAMAS 2015: 725-733
Coauthor Index
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