Conference on Robot Learning (CoRL 2020) Underway, Best Paper Finalists Announced

Conference on Robot Learning (CoRL 2020) Underway, Best Paper Finalists Announced

The 4th Conference on Robot Learning (CoRL) has announced the finalists for its Best Paper and Best System Paper awards. Since launching in 2017, CoRL has quickly become one of the world’s top academic gatherings at the intersection of robotics and machine learning: “a selective, single-track conference for robot learning research, covering a broad range of topics spanning robotics, ML and control, and including theory and applications.”

CoRL 2020 kicked off yesterday and runs virtually through November 18. This year saw 475 papers submitted, a 20 percent rise over 2019. There were 165 papers accepted for a 34.7 percent acceptance rate, up slightly from last year’s 27.6 percent.

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Best System Paper Award Finalists

SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

  • Institutions: Noah’s Ark Lab, Huawei Technologies; Shanghai Jiao Tong University; University College London
  • Authors: Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander Cowen Rivers, Zheng Tian, Daniel Palenicek, Haitham bou Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang

DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer

  • Institutions: University of California, Berkeley
  • Author: Ajay Kumar Tanwani
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Best Paper Award Finalists

Learning Latent Representations to Influence Multi-Agent Interaction

  • Institutions: Stanford University, Virginia Tech
  • Authors: Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh

Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions

  • Institutions: University of California, Berkeley; California Institute of Technology
  • Authors: Sarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames

Learning from Suboptimal Demonstration via Self-Supervised Reward Regression

  • Institutions: Georgia Institute of Technology
  • Authors: Letian Chen, Rohan Paleja, Matthew Gombolay

Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs

  • Institutions: Georgia Institute of Technology, Stanford University
  • Authors: Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou
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The CoRL 2020 Award Committee will present its Best Paper Award on Wednesday, November 18, the last day of the conference. All CoRL 2020 paper presentation videos and livestreams can be found on the CoRL YouTube channel.


Reporter: Fangyu Cai | Editor: Michael Sarazen


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Synced Report | A Survey of China’s Artificial Intelligence Solutions in Response to the COVID-19 Pandemic — 87 Case Studies from 700+ AI Vendors

This report offers a look at how China has leveraged artificial intelligence technologies in the battle against COVID-19. It is also available on Amazon KindleAlong with this report, we also introduced a database covering additional 1428 artificial intelligence solutions from 12 pandemic scenarios.

Click here to find more reports from us.


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We know you don’t want to miss any news or research breakthroughs. Subscribe to our popular newsletter Synced Global AI Weekly to get weekly AI updates.

Published at Tue, 17 Nov 2020 20:03:45 +0000

Conference on Robot Learning (CoRL 2020) Underway, Best Paper Finalists Announced

The 4th Conference on Robot Learning (CoRL) has announced the finalists for its Best Paper and Best System Paper awards. Since launching in 2017, CoRL has quickly become one of the world’s top academic gatherings at the intersection of robotics and machine learning: “a selective, single-track conference for robot learning research, covering a broad range of topics spanning robotics, ML and control, and including theory and applications.”

CoRL 2020 kicked off yesterday and runs virtually through November 18. This year saw 475 papers submitted, a 20 percent rise over 2019. There were 165 papers accepted for a 34.7 percent acceptance rate, up slightly from last year’s 27.6 percent.

image.png
image.png
42aa469144278fb18ee50107d338276.png

Best System Paper Award Finalists

SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

  • Institutions: Noah’s Ark Lab, Huawei Technologies; Shanghai Jiao Tong University; University College London
  • Authors: Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander Cowen Rivers, Zheng Tian, Daniel Palenicek, Haitham bou Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang

DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer

  • Institutions: University of California, Berkeley
  • Author: Ajay Kumar Tanwani
image.png

Best Paper Award Finalists

Learning Latent Representations to Influence Multi-Agent Interaction

  • Institutions: Stanford University, Virginia Tech
  • Authors: Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh

Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions

  • Institutions: University of California, Berkeley; California Institute of Technology
  • Authors: Sarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames

Learning from Suboptimal Demonstration via Self-Supervised Reward Regression

  • Institutions: Georgia Institute of Technology
  • Authors: Letian Chen, Rohan Paleja, Matthew Gombolay

Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs

  • Institutions: Georgia Institute of Technology, Stanford University
  • Authors: Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou
image.png

The CoRL 2020 Award Committee will present its Best Paper Award on Wednesday, November 18, the last day of the conference. All CoRL 2020 paper presentation videos and livestreams can be found on the CoRL YouTube channel.


Reporter: Fangyu Cai | Editor: Michael Sarazen


B4.png

Synced Report | A Survey of China’s Artificial Intelligence Solutions in Response to the COVID-19 Pandemic — 87 Case Studies from 700+ AI Vendors

This report offers a look at how China has leveraged artificial intelligence technologies in the battle against COVID-19. It is also available on Amazon KindleAlong with this report, we also introduced a database covering additional 1428 artificial intelligence solutions from 12 pandemic scenarios.

Click here to find more reports from us.


AI Weekly.png

We know you don’t want to miss any news or research breakthroughs. Subscribe to our popular newsletter Synced Global AI Weekly to get weekly AI updates.

Published at Tue, 17 Nov 2020 20:03:45 +0000

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