Sandy H. Huang

According to our database, Sandy H. Huang authored at least 25 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Data Release for: Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning.

Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess

Dataset, April, 2024

Learning agile soccer skills for a bipedal robot with deep reinforcement learning.

Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess

Sci. Robotics, 2024

Imitating Language via Scalable Inverse Reinforcement Learning.

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

CoRR, 2024

Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning.

Dhruva Tirumala, Markus Wulfmeier, Ben Moran, Sandy H. Huang, Jan Humplik, Guy Lever, Tuomas Haarnoja, Leonard Hasenclever, Arunkumar Byravan, Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess

CoRR, 2024

Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots.

Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle, Sandy H. Huang, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin A. Riedmiller

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Replay across Experiments: A Natural Extension of Off-Policy RL.

Dhruva Tirumala, Thomas Lampe, José Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Coherent Soft Imitation Learning.

Joe Watson, Sandy H. Huang, Nicolas Heess

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Understanding How Machines Can Learn Causal Overhypotheses.

Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Emily Rose Reagan, John F. Canny, Alison Gopnik

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

2022

Towards Understanding How Machines Can Learn Causal Overhypotheses.

Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B. Hamrick, John F. Canny, Nan Rosemary Ke, Alison Gopnik

CoRR, 2022

Learning Causal Overhypotheses through Exploration in Children and Computational Models.

Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Learning Causal Overhypotheses through Exploration in Children and Computational Models.

Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Nan Rosemary Ke, Sandy H. Huang, Bryanna Kaufmann, John F. Canny, Alison Gopnik

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning.

Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller

CoRR, 2021

A Constrained Multi-Objective Reinforcement Learning Framework.

Sandy H. Huang, Abbas Abdolmaleki, Giulia Vezzani, Philemon Brakel, Daniel J. Mankowitz, Michael Neunert, Steven Bohez, Yuval Tassa, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Exploring Exploration: Comparing Children with RL Agents in Unified Environments.

Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny

CoRR, 2020

A distributional view on multi-objective policy optimization.

Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning.

Sandy H. Huang, Martina Zambelli, Jackie Kay, Murilo F. Martins, Yuval Tassa, Patrick M. Pilarski, Raia Hadsell

CoRR, 2019

Enabling robots to communicate their objectives.

Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan

Auton. Robots, 2019

Nonverbal Robot Feedback for Human Teachers.

Sandy H. Huang, Isabella Huang, Ravi Pandya, Anca D. Dragan

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Human-AI Learning Performance in Multi-Armed Bandits.

Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Establishing Appropriate Trust via Critical States.

Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Expressing Robot Incapability.

Minae Kwon, Sandy H. Huang, Anca D. Dragan

Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, 2018

2017

Adversarial Attacks on Neural Network Policies.

Sandy H. Huang, Nicolas Papernot, Ian J. Goodfellow, Yan Duan, Pieter Abbeel

Proceedings of the 5th International Conference on Learning Representations, 2017

2015

Leveraging appearance priors in non-rigid registration, with application to manipulation of deformable objects.

Sandy H. Huang, Jia Pan, George Mulcaire, Pieter Abbeel

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Beyond lowest-warping cost action selection in trajectory transfer.

Dylan Hadfield-Menell, Alex X. Lee, Chelsea Finn, Eric Tzeng, Sandy H. Huang, Pieter Abbeel

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Unifying scene registration and trajectory optimization for learning from demonstrations with application to manipulation of deformable objects.

Alex X. Lee, Sandy H. Huang, Dylan Hadfield-Menell, Eric Tzeng, Pieter Abbeel

Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014