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ORCIDJun Luo 0009
Person information
- affiliation: Huawei Technologies Canada, Noah's Ark Lab, Toronto, Canada
Other persons with the same name
- Jun Luo — disambiguation page
- Jun Luo 0001
![[0000-0002-7036-5158]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-7036-5158")
— Nanyang Technological University, School of Computer Science and Engineering, Singapore - Jun Luo 0002 (aka: Jia-Jun Luo) — Chinese Academy of Sciences, Institute of Microelectronics, Beijing, China
- Jun Luo 0003 — Chongqing University, School of Computer Science, Chongqing, China
- Jun Luo 0004 — Harbin Institute of Technology, Department of Electrical Engineering, Harbin, China
- Jun Luo 0005 — Hohai University, Nanjing, China (and 1 more)
- Jun Luo 0006 — Chongqing University, College of Mechanical Engineering, State Key Laboratory of Mechanical Transmission, China (and 1 more)
- Jun Luo 0007 — Machine Intelligence Center Lenovo Group Limited, Hong Kong, China (and 1 more)
- Jun Luo 0008 — Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China
- Jun Luo 0010 — University of Pittsburgh, Intelligent Systems Program, School of Computing and Information, PA, USA,
- Jun Luo 0011 — National University of Defense Technology, School of Computer Science, Changsha, Hunan, China (and 1 more)
- Jun Luo 0012 — Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
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2020 – today
- 2024
[j4]Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip H. S. Torr, Yangchen Pan:
Label Alignment Regularization for Distribution Shift. J. Mach. Learn. Res. 25: 247:1-247:32 (2024)- 2023
- [j3]Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood:
Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation. Trans. Mach. Learn. Res. 2023 (2023) - [j2]Calarina Muslimani, Alex Lewandowski, Dale Schuurmans, Matthew E. Taylor, Jun Luo:
Reinforcement Teaching. Trans. Mach. Learn. Res. 2023 (2023) - [c18]Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White:
Auxiliary task discovery through generate-and-test. CoLLAs 2023: 703-714 - [c17]Amirmohammad Karimi, Jun Jin, Jun Luo, A. Rupam Mahmood, Martin Jägersand, Samuele Tosatto:
Dynamic Decision Frequency with Continuous Options. IROS 2023: 7545-7552 - 2022
- [j1]Daniel Graves, Johannes Günther, Jun Luo:
Affordance as general value function: a computational model. Adapt. Behav. 30(4): 307-327 (2022) - [c16]Wenhan Huang, Kai Li, Kun Shao, Tianze Zhou, Jun Luo, Dongge Wang, Hangyu Mao, Jianye Hao, Jun Wang, Xiaotie Deng:
Multiagent Q-learning with Sub-Team Coordination. AAMAS 2022: 1630-1632 - [c15]Jun Jin, Daniel Graves, Cameron Haigh, Jun Luo, Martin Jägersand:
Offline Learning of Counterfactual Predictions for Real-World Robotic Reinforcement Learning. ICRA 2022: 3616-3623 - [c14]Amir Rasouli, Tiffany Yau, Mohsen Rohani, Jun Luo:
Multi-Modal Hybrid Architecture for Pedestrian Action Prediction. IV 2022: 91-97 - [c13]Zichen Zhang, Jun Jin, Martin Jägersand, Jun Luo, Dale Schuurmans:
A Simple Decentralized Cross-Entropy Method. NeurIPS 2022 - [c12]Wenhan Huang, Kai Li, Kun Shao, Tianze Zhou, Matthew E. Taylor, Jun Luo, Dongge Wang, Hangyu Mao, Jianye Hao, Jun Wang, Xiaotie Deng:
Multiagent Q-learning with Sub-Team Coordination. NeurIPS 2022 - [c11]Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo:
Understanding and mitigating the limitations of prioritized experience replay. UAI 2022: 1561-1571 - [i28]Cameron Haigh, Zichen Zhang, Negar Hassanpour, Khurram Javed, Yingying Fu, Shayan Shahramian, Shawn Zhang, Jun Luo:
Drawing Inductor Layout with a Reinforcement Learning Agent: Method and Application for VCO Inductors. CoRR abs/2202.11798 (2022) - [i27]Elmira Amirloo Abolfathi, Amir Rasouli, Peter Lakner, Mohsen Rohani, Jun Luo:
LatentFormer: Multi-Agent Transformer-Based Interaction Modeling and Trajectory Prediction. CoRR abs/2203.01880 (2022) - [i26]Banafsheh Rafiee, Jun Jin, Jun Luo, Adam White:
What makes useful auxiliary tasks in reinforcement learning: investigating the effect of the target policy. CoRR abs/2204.00565 (2022) - [i25]Alex Lewandowski, Calarina Muslimani, Matthew E. Taylor, Jun Luo, Dale Schuurmans:
Reinforcement Teaching. CoRR abs/2204.11897 (2022) - [i24]Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood:
Memory-efficient Reinforcement Learning with Knowledge Consolidation. CoRR abs/2205.10868 (2022) - [i23]Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White:
Auxiliary task discovery through generate-and-test. CoRR abs/2210.14361 (2022) - [i22]Amir Rasouli, Randy Goebel, Matthew E. Taylor, Iuliia Kotseruba, Soheil Alizadeh, Tianpei Yang, Montgomery Alban, Florian Shkurti, Yuzheng Zhuang, Adam Scibior, Kasra Rezaee, Animesh Garg, David Meger, Jun Luo, Liam Paull, Weinan Zhang, Xinyu Wang, Xi Chen:
NeurIPS 2022 Competition: Driving SMARTS. CoRR abs/2211.07545 (2022) - [i21]Jun Jin, Hongming Zhang, Jun Luo:
Build generally reusable agent-environment interaction models. CoRR abs/2211.08234 (2022) - [i20]Ehsan Imani, Guojun Zhang, Jun Luo, Pascal Poupart, Yangchen Pan:
Label Alignment Regularization for Distribution Shift. CoRR abs/2211.14960 (2022) - [i19]Amirmohammad Karimi, Jun Jin, Jun Luo, A. Rupam Mahmood, Martin Jägersand, Samuele Tosatto:
Variable-Decision Frequency Option Critic. CoRR abs/2212.04407 (2022) - [i18]Zichen Zhang, Jun Jin, Martin Jägersand, Jun Luo, Dale Schuurmans:
A Simple Decentralized Cross-Entropy Method. CoRR abs/2212.08235 (2022) - 2021
- [c10]Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou-Ammar, Jun Wang, Matthew E. Taylor:
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems. AAMAS 2021: 51-56 - [c9]Elmira Amirloo Abolfathi, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart:
Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map. CVPR 2021: 8494-8503 - [c8]Amir Rasouli, Mohsen Rohani, Jun Luo:
Bifold and Semantic Reasoning for Pedestrian Behavior Prediction. ICCV 2021: 15580-15590 - [c7]Ershad Banijamali, Mohsen Rohani, Elmira Amirloo Abolfathi, Jun Luo, Pascal Poupart:
Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning. ICCV 2021: 15601-15610 - [c6]Tiffany Yau, Saber Malekmohammadi, Amir Rasouli, Peter Lakner, Mohsen Rohani, Jun Luo:
Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction. ICRA 2021: 8580-8586 - [c5]Fei Li, Xiangxu Li, Jun Luo, Shiwei Fan, Hongbo Zhang:
Open-set Intersection Intention Prediction for Autonomous Driving. ICRA 2021: 13092-13098 - [c4]Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh, Jun Jin, Jun Luo:
Learning robust driving policies without online exploration. ICRA 2021: 13186-13193 - [i17]Elmira Amirloo Abolfathi, Jun Luo, Peyman Yadmellat, Kasra Rezaee:
CoachNet: An Adversarial Sampling Approach for Reinforcement Learning. CoRR abs/2101.02649 (2021) - [i16]Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou-Ammar, Jun Wang, Matthew E. Taylor:
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems. CoRR abs/2102.07659 (2021) - [i15]Fei Li, Xiangxu Li, Jun Luo, Shiwei Fan, Hongbo Zhang:
Open-set Intersection Intention Prediction for Autonomous Driving. CoRR abs/2103.00140 (2021) - [i14]Elmira Amirloo Abolfathi, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart:
Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map. CoRR abs/2103.01039 (2021) - [i13]Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh, Jun Jin, Jun Luo:
Learning robust driving policies without online exploration. CoRR abs/2103.08070 (2021) - [i12]Tianze Zhou, Fubiao Zhang, Kun Shao, Kai Li, Wenhan Huang, Jun Luo, Weixun Wang, Yaodong Yang, Hangyu Mao, Bin Wang, Dong Li, Wulong Liu, Jianye Hao:
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment. CoRR abs/2106.00517 (2021) - [i11]Kasra Rezaee, Peyman Yadmellat, Masoud S. Nosrati, Elmira Amirloo Abolfathi, Mohammed Elmahgiubi, Jun Luo:
Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning. CoRR abs/2110.00650 (2021) - 2020
- [c3]Hangyu Mao, Wulong Liu, Jianye Hao, Jun Luo, Dong Li, Zhengchao Zhang, Jun Wang, Zhen Xiao:
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning. AAAI 2020: 7219-7226 - [c2]Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat M. Nguyen, Mohamed Elsayed, Haitham Ammar, Alexander I. Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, Dong Chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, Jun Wang:
SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. CoRL 2020: 264-285 - [i10]Ming Zhou, Jun Luo, Julian Villela, 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 M. 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 I. Cowen-Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou-Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang:
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR abs/2010.09776 (2020) - [i9]Daniel Graves, Johannes Günther, Jun Luo:
Affordance as general value function: A computational model. CoRR abs/2010.14289 (2020) - [i8]Jun Jin, Daniel Graves, Cameron Haigh, Jun Luo, Martin Jägersand:
Offline Learning of Counterfactual Perception as Prediction for Real-World Robotic Reinforcement Learning. CoRR abs/2011.05857 (2020) - [i7]Amir Rasouli, Tiffany Yau, Mohsen Rohani, Jun Luo:
Multi-Modal Hybrid Architecture for Pedestrian Action Prediction. CoRR abs/2012.00514 (2020) - [i6]Tiffany Yau, Saber Malekmohammadi, Amir Rasouli, Peter Lakner, Mohsen Rohani, Jun Luo:
Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction. CoRR abs/2012.02148 (2020) - [i5]Amir Rasouli, Mohsen Rohani, Jun Luo:
Pedestrian Behavior Prediction via Multitask Learning and Categorical Interaction Modeling. CoRR abs/2012.03298 (2020) - [i4]Amir Rasouli, Tiffany Yau, Peter Lakner, Saber Malekmohammadi, Mohsen Rohani, Jun Luo:
PePScenes: A Novel Dataset and Baseline for Pedestrian Action Prediction in 3D. CoRR abs/2012.07773 (2020) - [i3]Ershad Banijamali, Mohsen Rohani, Elmira Amirloo Abolfathi, Jun Luo, Pascal Poupart:
Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning. CoRR abs/2012.13478 (2020) - [i2]Daniel Graves, Jun Jin, Jun Luo:
LISPR: An Options Framework for Policy Reuse with Reinforcement Learning. CoRR abs/2012.14942 (2020)
2010 – 2019
- 2019
- [c1]Kasra Rezaee, Peyman Yadmellat, Masoud S. Nosrati, Elmira Amirloo Abolfathi, Mohammed Elmahgiubi, Jun Luo:
Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning. ITSC 2019: 1800-1806 - [i1]Hangyu Mao, Wulong Liu, Jianye Hao, Jun Luo, Dong Li, Zhengchao Zhang, Jun Wang, Zhen Xiao:
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning. CoRR abs/1912.01160 (2019)
Coauthor Index
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