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Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method

Oct 15, 2020
Zuxin Liu, Hongyi Zhou, Baiming Chen, Sicheng Zhong, Martial Hebert, Ding Zhao

* 9 pages, 6 figures 

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Rare-Event Simulation for Neural Network and Random Forest Predictors

Oct 10, 2020
Yuanlu Bai, Zhiyuan Huang, Henry Lam, Ding Zhao


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Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation

Sep 25, 2020
Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, Ding Zhao

* 8 pages, 7 figures 

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MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments

Jul 30, 2020
Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao

* 6 pages, accepted at the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020) 

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Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy

Jul 01, 2020
Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao


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Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

Jun 29, 2020
Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao

* 16 pages, 6 figures 

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Robust Unsupervised Learning of Temporal Dynamic Interactions

Jun 18, 2020
Aritra Guha, Rayleigh Lei, Jiacheng Zhu, XuanLong Nguyen, Ding Zhao


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Dynamic Sparsity Neural Networks for Automatic Speech Recognition

May 16, 2020
Zhaofeng Wu, Ding Zhao, Qiao Liang, Jiahui Yu, Anmol Gulati, Ruoming Pang

* Submitted to INTERSPEECH 2020 

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Delay-Aware Multi-Agent Reinforcement Learning

May 11, 2020
Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao


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Delay-Aware Model-Based Reinforcement Learning for Continuous Control

May 11, 2020
Baiming Chen, Mengdi Xu, Liang Li, Ding Zhao


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A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency

Mar 28, 2020
Tara N. Sainath, Yanzhang He, Bo Li, Arun Narayanan, Ruoming Pang, Antoine Bruguier, Shuo-yiin Chang, Wei Li, Raziel Alvarez, Zhifeng Chen, Chung-Cheng Chiu, David Garcia, Alex Gruenstein, Ke Hu, Minho Jin, Anjuli Kannan, Qiao Liang, Ian McGraw, Cal Peyser, Rohit Prabhavalkar, Golan Pundak, David Rybach, Yuan Shangguan, Yash Sheth, Trevor Strohman, Mirko Visontai, Yonghui Wu, Yu Zhang, Ding Zhao

* In Proceedings of IEEE ICASSP 2020 

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Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method

Mar 02, 2020
Wenhao Ding, Minjun Xu, Ding Zhao

* Submitted to IROS 2020 

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Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process

Oct 17, 2019
Jiacheng Zhu, Shenghao Qin, Wenshuo Wang, Ding Zhao

* 7 pages, 5 figures, submitted to ICRA 2020 

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Recurrent Attentive Neural Process for Sequential Data

Oct 17, 2019
Shenghao Qin, Jiacheng Zhu, Jimmy Qin, Wenshuo Wang, Ding Zhao

* 12 pages, 6 figures, NeurIPS 2019 Workshop 

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Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression

Oct 08, 2019
Weiyang Zhang, Wenshuo Wang, Ding Zhao


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CMTS: Conditional Multiple Trajectory Synthesizer for Generating Safety-critical Driving Scenarios

Oct 02, 2019
Wenhao Ding, Mengdi Xu, Ding Zhao

* Submitted to ICRA 2020, 8 pages, 7 figures 

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How to Evaluate Proving Grounds for Self-Driving? A Quantitative Approach

Sep 24, 2019
Rui Chen, Mansur Arief, Weiyang Zhang, Ding Zhao


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Active Learning for Risk-Sensitive Inverse Reinforcement Learning

Sep 23, 2019
Rui Chen, Wenshuo Wang, Zirui Zhao, Ding Zhao

* 8 pages without acknowledgment, 7 figures, submitted to RA-L and ICRA 2020 for the IEEE Robotics and Automation Letters (RA-L) 

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How to Evaluate Self-Driving Testing Ground? A Quantitative Approach

Sep 20, 2019
Rui Chen, Mansur Arief, Weiyang Zhang, Ding Zhao


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A General Framework of Learning Multi-Vehicle Interaction Patterns from Videos

Jul 17, 2019
Chengyuan Zhang, Jiacheng Zhu, Wenshuo Wang, Ding Zhao

* 2019 IEEE Intelligent Transportation Systems Conference (ITSC) 

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Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field

Jun 25, 2019
Yaohui Guo, Vinay Varma Kalidindi, Mansur Arief, Wenshuo Wang, Jiacheng Zhu, Huei Peng, Ding Zhao


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Assessing Modeling Variability in Autonomous Vehicle Accelerated Evaluation

Apr 19, 2019
Zhiyuan Huang, Mansur Arief, Henry Lam, Ding Zhao


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Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach

Apr 07, 2019
Zuxin Liu, Mansur Arief, Ding Zhao

* 7 pages including the references, accepted by International Conference on Robotics and Automation (ICRA), 2019 

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Clustering of Driving Encounter Scenarios Using Connected Vehicle Trajectories

Mar 16, 2019
Wenshuo Wang, Aditya Ramesh, Ding Zhao

* 12 pages, 11 figures 

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A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters

Feb 24, 2019
Wenhao Ding, Wenshuo Wang, Ding Zhao

* 6 pages, accepted by ICRA 2019 

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