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检索条件"机构=National Key Laboratory for Parallel and Distributed Processing"
1142 条 记 录,以下是141-150 订阅
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ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations
ST-PINN: A Self-Training Physics-Informed Neural Network for...
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International Joint Conference on Neural Networks (IJCNN)
作者: Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhoui Jie Liu Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha 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...
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parallel Implementation of SHA256 on Multizone Heterogeneous Systems
Parallel Implementation of SHA256 on Multizone Heterogeneous...
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IEEE International Conference on Big Data and Cloud Computing (BdCloud)
作者: Yongtao Luo Jie Liu Tiaojie Xiao Chunye Gong Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Digitizing program for Frontier Equipment National University of Defense Technology Changsha China National Supercomputer Center in Tianjin Tianjin China
SHA-256 plays an important role in widely used applications, such as data security, data integrity, digital signatures, and cryptocurrencies. However, most of the current optimized implementations of SHA-256 are based...
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XGrad: Boosting Gradient-Based Optimizers With Weight Prediction
arXiv
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arXiv 2023年
作者: Guan, Lei Li, Dongsheng Shi, Yanqi Meng, Jian The Department of Mathematics National University of Defense Technology Changsha China The National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China
In this paper, we propose a general deep learning training framework XGrad which introduces weight prediction into the popular gradient-based optimizers to boost their convergence and generalization when training the ... 详细信息
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A Counterfactual Ultrasound Anti-Interference Self-Supervised Network for B-mode Ultrasound Tongue Extraction
A Counterfactual Ultrasound Anti-Interference Self-Supervise...
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International Conference on Acoustics, Speech, and Signal processing (ICASSP)
作者: Yan Jia Yuqing Cheng Kele Xu Yong Dou Peng Qiao Zhouyu He National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha China College of Systems Engineering National University of Defense Technology Changsha China
B-mode ultrasound tongue imaging is a non-invasive and real-time method for visualizing vocal tract deformation. However, accurately extracting the tongue’s surface contour remains a significant challenge due to the ... 详细信息
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ACCURATE AND EFFICIENT FINE-TUNING OF QUANTIZED LARGE LANGUAGE MODELS THROUGH OPTIMAL BALANCE
arXiv
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arXiv 2024年
作者: Shen, Ao Wang, Qiang Lai, Zhiquan Li, Xionglve Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Hunan Changsha410073 China College of computer National University of Defense Technology Hunan Changsha410073 China
Large Language Models (LLMs) have demonstrated impressive performance across various domains. However, the enormous number of model parameters makes fine-tuning challenging, significantly limiting their application an... 详细信息
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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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Simultaneously Learning Syntactic Dependency and Semantics Reasonability for Relation Extraction
Simultaneously Learning Syntactic Dependency and Semantics R...
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International Conference on Image, Vision and Intelligent Systems, ICIVIS 2021
作者: Wang, Xin Yin, Nan Zhang, Xiang Bai, Xinyi Luo, Zhigang College of Computer National University of Defense Technology Changsha China Institute for Quantum and State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha China
Relation extraction as an important Natural Language processing (NLP) task is to identify relations between named entities in text. Recently, graph convolutional networks over dependency trees have been widely used to... 详细信息
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KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion
arXiv
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arXiv 2024年
作者: Wang, Yilin Hu, Minghao Huang, Zhen Li, Dongsheng Yang, Dong Lu, Xicheng Defense Innovation Institute Academy of Military Sciences China Information Research Center of Military Science China National Key Laboratory of Parallel and Distributed Computing China
The goal of knowledge graph completion (KGC) is to predict missing facts among entities. Previous methods for KGC re-ranking are mostly built on non-generative language models to obtain the probability of each candida... 详细信息
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Graph Structure Learning via Transfer Entropy for Multivariate Time Series Anomaly Detection
Graph Structure Learning via Transfer Entropy for Multivaria...
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International Conference on Acoustics, Speech, and Signal processing (ICASSP)
作者: Mingyu Liu Yijie Wang Xiaohui Zhou Yongjun Wang National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha China College of Computer Science and Technology National University of Defense Technology Changsha China
Multivariate time series anomaly detection (MTAD) poses a challenge due to temporal and feature dependencies. The critical aspects of enhancing the detection performance lie in accurately capturing the dependencies be... 详细信息
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High-performance Network Traffic Classification Based on Graph Neural Network
High-performance Network Traffic Classification Based on Gra...
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IEEE Information Technology, Networking, Electronic and Automation Control Conference
作者: Bo Pang Yongquan Fu Siyuan Ren Yan Jia College of Computer Science and Technology Harbin Institute of Technology Shenzhen China National Key Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changesha China Peng Cheng Laboratory Shen Zhen China
Network traffic classification is crucial for network security and network management and is one of the most important network tasks. Current state-of-the-art traffic classifiers are based on deep learning models to a... 详细信息
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