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检索条件"机构=The National Key Laboratory of Parallel and Distributed Computing"
528 条 记 录,以下是251-260 订阅
排序:
Deep Learning-based Cooperative Trail Following for Multi-Robot System
Deep Learning-based Cooperative Trail Following for Multi-Ro...
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2018 International Joint Conference on Neural Networks, IJCNN 2018
作者: Geng, Mingyang Li, Yiying Ding, Bo Wang, And Huaimin National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology ChangSha China
Following trails in the wild is an essential capability of out-door autonomous mobile robots. Recently, deep learningbased approaches have made great advancements in this field. However, the existing research only foc... 详细信息
来源: 评论
Unsupervised Learning-based Depth Estimation aided Visual SLAM Approach
arXiv
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arXiv 2019年
作者: Geng, Mingyang Shang, Suning Ding, Bo Wang, Huaimin Zhang, Pengfei Zhang, Lei National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology China National Key Laboratory of Integrated Automation of Process Industry Northeastern University China
Existing visual-based SLAM systems mainly utilize the three-dimensional environmental depth information from RGB-D cameras to complete the robotic synchronization localization and map construction task. However, the R... 详细信息
来源: 评论
Succinct Representations in Collaborative Filtering: A Case Study using Wavelet Tree on 1,000 Cores
Succinct Representations in Collaborative Filtering: A Case ...
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IEEE International Conference on parallel and distributed computing, Applications and Technologies (PDCAT)
作者: Xiangjun Peng Qingfeng Wang Xu Sun Chunye Gong Yaohua Wang User-Centric Computing Group University of Nottingham Ningbo China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology
User-Item (U-I) matrix has been used as the dominant data infrastructure of Collaborative Filtering (CF). To reduce space consumption in runtime and storage, caused by data sparsity and growing need to accommodate sid... 详细信息
来源: 评论
Modeling complex relationship paths for knowledge graph completion
Modeling complex relationship paths for knowledge graph comp...
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作者: Zeng, Ping Tan, Qingping Meng, Xiankai Zhang, Haoyu Xu, Jianjun College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing Changsha China
Determining the validity of knowledge triples and filling in the missing entities or relationships in the knowledge graph are the crucial tasks for large-scale knowledge graph completion. So far, the main solutions us... 详细信息
来源: 评论
GREYONE: data flow sensitive fuzzing  20
GREYONE: data flow sensitive fuzzing
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Proceedings of the 29th USENIX Conference on Security Symposium
作者: Shuitao Gan Chao Zhang Peng Chen Bodong Zhao Xiaojun Qin Dong Wu Zuoning Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Institute for Network Science and Cyberspace Tsinghua University and Beijing National Research Center for Information Science and Technology ByteDance AI lab Institute for Network Science and Cyberspace Tsinghua University National Research Center of Parallel Computer Engineering and Technology
Data flow analysis (e.g., dynamic taint analysis) has proven to be useful for guiding fuzzers to explore hard-to-reach code and find vulnerabilities. However, traditional taint analysis is labor-intensive, inaccurate ...
来源: 评论
Attention-based fault-tolerant approach for multi-agent reinforcement learning systems
arXiv
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arXiv 2019年
作者: Geng, Mingyang Xu, Kele Li, Yiying Liu, Shuqi Ding, Bo Wang, Huaimin National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory of Big Data Management and Analysis Northeastern University Shenyang110000 China
The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents. In many real-world applications, the agents c... 详细信息
来源: 评论
Mobile Robot Object Recognition in The Internet of Things based on Fog computing
Mobile Robot Object Recognition in The Internet of Things ba...
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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)
作者: Meixia Fu Songlin Sun Kaili Ni Xiaoying Hou National Engineering Laboratory for Mobile Network Security Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service (BUPT)
Mobile robot object recognition has attracted significant attention in the internet of things recently, in which there are many challenging tasks, such as the objects, the communication networks and the computer syste... 详细信息
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Towards a uniform architecture for the efficient implementation of 2D and 3D deconvolutional neural networks on FPGAS
arXiv
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arXiv 2019年
作者: Wang, Deguang Shen, Junzhong Wen, Mei Zhang, Chunyuan College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory for Parallel Distributed ProcessingNational University of Defense Technology Changsha410073 China
Three-dimensional deconvolution is widely used in many computer vision applications. However, most previous works have only focused on accelerating 2D deconvolutional neural networks (DCNNs) on FPGAs, while the accele... 详细信息
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Reinforcement Learning Based Antenna Selection in User-Centric Massive MIMO
Reinforcement Learning Based Antenna Selection in User-Centr...
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IEEE Conference on Vehicular Technology (VTC)
作者: Xinxin Chai Hui Gao Ji Sun Xin Su Tiejun Lv Jie Zeng Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China Ministry of Industry and Information Technology Institute of Telecommunications Beijing China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China
In this paper, we consider a user-centric massive multiple-input multiple-output (UC-MMIMO) system, wherein the optimal antenna selection (AS) is very complicated, because of the huge number of deployed antennas. Trad... 详细信息
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Modulation Recognition based on Incremental Deep Learning
Modulation Recognition based on Incremental Deep Learning
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International Conference on Mechanical, Control and Computer Engineering (ICMCCE)
作者: Yong Yang Menghan Chen XiaoYa Wang Piming Ma The 54th Research Institute of CETC Shijiazhuang China School of Information Science and Engineering Shandong University Qingdao China School of Information and Communication Engineering National Engineering Laboratory for Mobile Network Security Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications line Beijing China
Incremental learning has emerged to solve the problem of incrementally updating the classification model as the number of data classes grows. There are many challenges in incremental learning such as catastrophic forg... 详细信息
来源: 评论