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检索条件"机构=Laboratory for Parallel and Distributed Processing"
1115 条 记 录,以下是81-90 订阅
排序:
Offline Imitation Learning Using Reward-free Exploratory Data  22
Offline Imitation Learning Using Reward-free Exploratory Dat...
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Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence
作者: Hao Wang Dawei Feng Bo Ding Wei Li College of Computer National University of Defense Technology China National Laboratory for Parallel and Distributed Processing National University of Defense Technology China Independent Researcher China
Offline imitative learning(OIL) is often used to solve complex continuous decision-making tasks. For these tasks such as robot control, automatic driving and etc., it is either difficult to design an effective reward ... 详细信息
来源: 评论
Sparse Matrix Reordering Method Selection with parallel Computing and Deep Learning
Sparse Matrix Reordering Method Selection with Parallel Comp...
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International Joint Conference on Neural Networks (IJCNN)
作者: Rui Xia Jihu Guo Huajian Zhang Shun Yang Qinglin Wang Jie Liu College of Computer Science and Techonology National University of Defense Technology Changsha China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology
Sparse matrix reordering is an important step in Cholesky decomposition. By reordering the rows and columns of the matrix, the time of computation and storage cost can be greatly reduced. With the proposal of various ... 详细信息
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MPS: A Multiple Poisoned Samples Selection Strategy in Backdoor Attack
MPS: A Multiple Poisoned Samples Selection Strategy in Backd...
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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
作者: Weihong Zou Shigeng Zhang Weiping Wang Jian Zhang Xuan Liu Schoosl of Computer Science and Engineering Central South University Science and Technology on Parallel and Distributed Processing Laboratory (PDL) College of Computer Science and Electronic Engineering Hunan University
Recently there has been many studies on backdoor attacks, which involve injecting poisoned samples into the training set in order to embed backdoors into the model. Existing multiple poisoned samples attacks usually r... 详细信息
来源: 评论
Merak: An Efficient distributed DNN Training Framework with Automated 3D parallelism for Giant Foundation Models
arXiv
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arXiv 2022年
作者: Lai, Zhiquan Li, Shengwei Tang, Xudong Ge, Keshi Liu, Weijie Duan, Yabo Qiao, Linbo Li, Dongsheng The National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology in Changsha Hunan China
Foundation models are in the process of becoming the dominant deep learning technology. Pretraining a foundation model is always time-consuming due to the large scale of both the model parameter and training dataset. ... 详细信息
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SCGraph: Accelerating Sample-based GNN Training by Staged Caching of Features on GPUs
SCGraph: Accelerating Sample-based GNN Training by Staged Ca...
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IEEE International Conference on Big Data and Cloud Computing (BdCloud)
作者: Yuqi He Zhiquan Lai Zhejiang Ran Lizhi Zhang Dongsheng Li National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha China
Graph neural networks (GNNs) have been becoming important tools for processing structured graph data and successfully applied to multiple graph-based application scenarios. The existing GNN systems adopt sample-based ... 详细信息
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Feature and Performance Comparison of FaaS Platforms  14
Feature and Performance Comparison of FaaS Platforms
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14th IEEE International Conference on Software Engineering and Service Science, ICSESS 2023
作者: Ma, Penghui Shi, Peichang Yi, Guodong College of Computer Science National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China College of Computer Science National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems Changsha410073 China Xiangjiang Lab Changsha410073 China School of Advanced Interdisciplinary Studies Hunan University of Technology and Business Changsha410073 China
With serverless computing offering more efficient and cost-effective application deployment, the diversity of serverless platforms presents challenges to users, including platform lock-in and costly migration. Moreove... 详细信息
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AUXILIARY-TASKS LEARNING FOR PHYSICS-INFORMED NEURAL NETWORK-BASED PARTIAL DIFFERENTIAL EQUATIONS SOLVING
arXiv
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arXiv 2023年
作者: Yan, Junjun Chen, Xinhai Wang, Zhichao Zhou, Enqiang Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China
Physics-informed neural networks (PINNs) have emerged as promising surrogate modes for solving partial differential equations (PDEs). Their effectiveness lies in the ability to capture solution-related features throug... 详细信息
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Bi-Objective Scheduling Algorithm for Hybrid Workflow in JointCloud
Bi-Objective Scheduling Algorithm for Hybrid Workflow in Joi...
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IEEE International Conference on Joint Cloud Computing (JCC)
作者: Rui Li Huaimin Wang Peichang Shi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China State Key Laboratory of Complex & Critica Software Environment College of Computer Science National University of Defense Technology Changsha China
Big data workflows are widely used in IoT, recommended systems, and real-time vision applications, and they continue to grow in complexity. These hybrid workflows consist of both resource-intensive batch jobs and late... 详细信息
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ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations
arXiv
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arXiv 2023年
作者: Yan, Junjun Chen, Xinhai Wang, Zhichao Zhoui, Enqiang Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China
Partial differential equations (PDEs) are an essential computational kernel in physics and engineering. With the advance of deep learning, physics-informed neural networks (PINNs), as a mesh-free method, have shown gr... 详细信息
来源: 评论
A Fast Adversarial Sample Detection Approach for Industrial Internet-of-Things Applications
A Fast Adversarial Sample Detection Approach for Industrial ...
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International Workshop on Quality of Service
作者: Shigeng Zhang Yudong Li Shuxin Chen Xuan Li Jian Zhang School of Computer Science and Engineering Central South University College of Computer Science and Electronic Engineering Hunan University The Science and Technology on Parallel and Distributed Processing Laboratory (PDL) China
Adversarial attacks reveal the inherent vulnerability of deep neural networks, which face serious security issues for their security. Among them, the attack against the Deep Neural Network (DNN) application used in th...
来源: 评论