Todd Hester - RankMe

39 papers A* 6A 2C 7Journal 16Unranked 6

Year	Rank	Type	Title / Venue / Authors
2021	J	`jnl`	Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
2021	A	`conf`	ETA Prediction with Graph Neural Networks in Google Maps. CIKM Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Velickovic
2021	J	`jnl`	ETA Prediction with Graph Neural Networks in Google Maps. CoRR Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Velickovic
2020	J	`jnl`	An empirical investigation of the challenges of real-world reinforcement learning. CoRR Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
2020	A*	`conf`	Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller
2019	A*	`conf`	A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. ICRA Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz
2019	J	`jnl`	Challenges of Real-World Reinforcement Learning. CoRR Gabriel Dulac-Arnold, Daniel J. Mankowitz, Todd Hester
2019	J	`jnl`	Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller
2018	J	`jnl`	A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. CoRR Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz
2018	A*	`conf`	Deep Q-learning From Demonstrations. AAAI Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
2018	J	`jnl`	Observe and Look Further: Achieving Consistent Performance on Atari. CoRR Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, Gabriel Barth-Maron, Hado van Hasselt, John Quan, Mel Vecerík, Matteo Hessel, Rémi Munos, Olivier Pietquin
2018	J	`jnl`	Safe Exploration in Continuous Action Spaces. CoRR Gal Dalal, Krishnamurthy Dvijotham, Matej Vecerík, Todd Hester, Cosmin Paduraru, Yuval Tassa
2017	J	`jnl`	Intrinsically motivated model learning for developing curious robots. Artif. Intell. Todd Hester, Peter Stone
2017	J	`jnl`	Learning from Demonstrations for Real World Reinforcement Learning. CoRR Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
2017	J	`jnl`	Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. CoRR Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller
2016	J	`jnl`	Adaptive Lambda Least-Squares Temporal Difference Learning. CoRR Timothy A. Mann, Hugo Penedones, Shie Mannor, Todd Hester
2013	A	`conf`	Learning exploration strategies in model-based reinforcement learning. AAMAS Todd Hester, Manuel Lopes, Peter Stone
2013	—	`book`	TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains. Todd Hester
2013	J	`jnl`	TEXPLORE: real-time sample-efficient reinforcement learning for robots. Mach. Learn. Todd Hester, Peter Stone
2013	C	`conf`	The 2012 UT Austin Villa Code Release. RoboCup Samuel Barrett, Katie Long Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, Peter Stone
2013	C	`conf`	The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots. RoboCup Todd Hester, Peter Stone
2012	—	`conf`	Intrinsically motivated model learning for a developing curious agent. ICDL-EPIROB Todd Hester, Peter Stone
2012	—	`ch.`	Learning and Using Models. Reinforcement Learning Todd Hester, Peter Stone
2012	A*	`conf`	RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for robot control. ICRA Todd Hester, Michael J. Quinlan, Peter Stone
2012	—	`conf`	TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. AAAI Spring Symposium: Designing Intelligent Robots Todd Hester, Peter Stone
2012	C	`conf`	UT Austin Villa 2012: Standard Platform League World Champions. RoboCup Samuel Barrett, Katie Long Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, Peter Stone
2011	J	`jnl`	A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control CoRR Todd Hester, Michael J. Quinlan, Peter Stone
2010	J	`jnl`	A Novel Approach to Monitor Rehabilitation Outcomes in Stroke Survivors Using Wearable Technology. Proc. IEEE Shyamal Patel, Richard Hughes, Todd Hester, Joel Stein, Metin Akay, Jennifer G. Dy, Paolo Bonato
2010	A*	`conf`	Generalized model learning for Reinforcement Learning on a humanoid robot. ICRA Todd Hester, Michael J. Quinlan, Peter Stone
2010	—	`conf`	Real time targeted exploration in large domains. ICDL Todd Hester, Peter Stone
2009	—	`conf`	Generalized model learning for reinforcement learning in factored domains. AAMAS (2) Todd Hester, Peter Stone
2009	C	`conf`	Three Humanoid Soccer Platforms: Comparison and Synthesis. RoboCup Shivaram Kalyanakrishnan, Todd Hester, Michael J. Quinlan, Yinon Bentor, Peter Stone
2008	A*	`conf`	Negative information and line observations for Monte Carlo localization. ICRA Todd Hester, Peter Stone
2008	J	`jnl`	Processing Wearable Sensor Data to Optimize Deep-Brain Stimulation. IEEE Pervasive Comput. Shyamal Patel, Todd Hester, Richard Hughes, Nancy Huggins, Alice Flaherty, David G. Standaert, John Growdon, Paolo Bonato
2008	—	`conf`	The utility of temporal abstraction in reinforcement learning. AAMAS (1) Nicholas K. Jong, Todd Hester, Peter Stone
2006	C	`conf`	Analysis of the Severity of Dyskinesia in Patients with Parkinson's Disease via Wearable Sensors. BSN Shyamal Patel, Delsey M. Sherrill, Richard Hughes, Todd Hester, Theresa Lie-Nemeth, Paolo Bonato, David G. Standaert, Nancy Huggins
2006	—	`conf`	Identification of Tasks Performed by Stroke Patients Using a Mobility Assistive Device. EMBC Todd Hester, Delsey M. Sherrill, Mathieu Hamel, Karine Perreault, Patrick Boissy, Paolo Bonato
2006	C	`conf`	Using Wearable Sensors to Analyze the Quality of Use of Mobility Assistive Devices. BSN Todd Hester, Delsey M. Sherrill, Paolo Bonato, Mathieu Hamel, Karine Perreault, Patrick Boissy
2006	C	`conf`	Using Wearable Sensors to Measure Motor Abilities following Stroke. BSN Todd Hester, Richard Hughes, Delsey M. Sherrill, Bethany Knorr, Metin Akay, Joel Stein, Paolo Bonato