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Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling


Jun 19, 2021
Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

* 10 pages, 5 figures 

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CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing


Jun 17, 2021
Fan Wu, Linyi Li, Zijian Huang, Yevgeniy Vorobeychik, Ding Zhao, Bo Li

* 25 pages, 7 figures 

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Semantically Controllable Scene Generation with Guidance of Explicit Knowledge


Jun 08, 2021
Wenhao Ding, Bo Li, Kim Ji Eun, Ding Zhao

* 10 pages, 6 figures, Submitted to NeurIPS 2021 

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Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles


May 02, 2021
Sharad Chitlangia, Zuxin Liu, Akhil Agnihotri, Ding Zhao


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Personalized Keyphrase Detection using Speaker and Environment Information


Apr 28, 2021
Rajeev Rikhye, Quan Wang, Qiao Liang, Yanzhang He, Ding Zhao, Yiteng, Huang, Arun Narayanan, Ian McGraw


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Functional Optimal Transport: Mapping Estimation and Domain Adaptation for Functional data


Feb 09, 2021
Jiacheng Zhu, Aritra Guha, Mengdi Xu, Yingchen Ma, Rayleigh Lei, Vincenzo Loffredo, XuanLong Nguyen, Ding Zhao

* 10 pages, 6 figures, 2 tables 

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Context-Aware Safe Reinforcement Learning for Non-Stationary Environments


Jan 02, 2021
Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Ding Zhao


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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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