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Conditional Goal-Oriented Trajectory Prediction for Interacting Vehicles 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者:  Li, Ding;  Zhang, Qichao;  Lu, Shuai;  Pan, Yifeng;  Zhao, Dongbin
收藏  |  浏览/下载：93/0  |  提交时间：2023/12/21
Trajectory  Predictive models  Behavioral sciences  Pipelines  Task analysis  Feature extraction  Vehicle dynamics  Conditional prediction  goal-oriented trajectory prediction  hierarchical vectorized representation  joint trajectory prediction  marginal prediction  
Stacked BNAS: Rethinking Broad Convolutional Neural Network for Neural Architecture Search 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 0, 期号: 0, 页码: 0
作者:  Zixiang, Ding;  Yaran, Chen;  Nannan, Li;  Dongbin, Zhao;  C.L.Philip Chen,
Adobe PDF(764Kb)  |  收藏  |  浏览/下载：180/28  |  提交时间：2022/01/07
broad neural architecture search, stacked broad convolutional neural network, knowledge embedding search, image classification.  
UNMAS: Multiagent Reinforcement Learning for Unshaped Cooperative Scenarios 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Chai, Jiajun;  Li, Weifan;  Zhu, Yuanheng;  Zhao, Dongbin;  Ma, Zhe;  Sun, Kewu;  Ding, Jishiyu
Adobe PDF(3402Kb)  |  收藏  |  浏览/下载：215/23  |  提交时间：2022/01/27
Multi-agent systems  Training  Task analysis  Reinforcement learning  Sun  Learning systems  Semantics  Centralized training with decentralized execution (CTDE)  multiagent  reinforcement learning  StarCraft II  
BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 期号: 0, 页码: 0
作者:  Ding ZX(丁子祥);  Yaran, Chen;  Nannan, Li;  Dingbin, Zhao;  Zhiquan, Sun;  C. L. Philip Chen
Adobe PDF(2713Kb)  |  收藏  |  浏览/下载：147/39  |  提交时间：2022/01/06
Broad convolutional neural network (BCNN), image classification, neural architecture search (NAS), reinforcement learning (RL)  
Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 8, 页码: 3658-3668
作者:  Wang, Huanqing;  Liu, Peter Xiaoping;  Li, Shuai;  Wang, Ding
收藏  |  浏览/下载：169/0  |  提交时间：2019/12/16
Adaptive neural control  backstepping  nonlower triangular nonlinear systems  output-feedback control  
Manifold Regularized Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 932-943
作者:  Li, Hongliang;  Liu, Derong;  Wang, Ding
收藏  |  浏览/下载：173/0  |  提交时间：2018/10/10
Adaptive Dynamic Programming  Approximate Dynamic Programming  Approximate Policy Iteration (Api)  Manifold Regularization  Reinforcement Learning (Rl)  
A Fast Algorithm of Convex Hull Vertices Selection for Online Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 792-806
作者:  Ding, Shuguang;  Nie, Xiangli;  Qiao, Hong;  Zhang, Bo
浏览  |  Adobe PDF(3029Kb)  |  收藏  |  浏览/下载：379/128  |  提交时间：2017/12/30
Convex Hull Decomposition  Kernel  Online Classification  Projection  
Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 6, 页码: 1323-1334
作者:  Liu, Derong;  Li, Hongliang;  Wang, Ding
Adobe PDF(1114Kb)  |  收藏  |  浏览/下载：277/82  |  提交时间：2015/09/17
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Neural Networks  Neurodynamic Programming  Nonlinear Systems  Optimal Control  
Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 卷号: 25, 期号: 2, 页码: 418-428
作者:  Liu, Derong;  Wang, Ding;  Li, Hongliang
Adobe PDF(1311Kb)  |  收藏  |  浏览/下载：249/99  |  提交时间：2015/08/12
Adaptive Dynamic Programming  Decentralized Control  Large-scale Systems  Neural Networks  Nonlinear Interconnected Systems  Optimal Control  Policy Iteration  Reinforcement Learning