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检索条件"任意字段=Neural Network and Distributed Processing"
6427 条 记 录,以下是41-50 订阅
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SMEGA2: distributed Asynchronous Deep neural network Training With a Single Momentum Buffer  51
SMEGA<SUP>2</SUP>: Distributed Asynchronous Deep Neural Netw...
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51st International Conference on Parallel processing (ICPP)
作者: Cohen, Rafi Hakimi, Ido Schuster, Assaf Technion Israel Inst Technol Dept Comp Sci Haifa Israel
As the field of deep learning progresses, and neural networks become larger, training them has become a demanding and time consuming task. To tackle this problem, distributed deep learning must be used to scale the tr... 详细信息
来源: 评论
neural network-BASED COMPRESSION FRAMEWORK FOR DOA ESTIMATION EXPLOITING distributed ARRAY  47
NEURAL NETWORK-BASED COMPRESSION FRAMEWORK FOR DOA ESTIMATIO...
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47th IEEE International Conference on Acoustics, Speech and Signal processing (ICASSP)
作者: Pavel, Saidur R. Zhang, Yimin D. Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA
distributed array consisting of multiple subarrays is attractive for high-resolution direction-of-arrival (DOA) estimation when a large-scale array is infeasible. To achieve effective distributed DOA estimation, it is... 详细信息
来源: 评论
Drowsiness Detection for Drivers using Hybrid T-distributed Stochastic Neighbor Embedding with Convolutional neural network  2
Drowsiness Detection for Drivers using Hybrid T-Distributed ...
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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023
作者: Balakrishnan, D. Mariappan, Umasree Nikhitha, Balabhadra Akshitha, Bokkisam Visali, Bedamsetty Snehalatha, Bandikattu Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu Krishnankoil626126 India Sri Vidya College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Virudhunagar626005 India
Drowsiness Detection (DD) is the procedure of identifying signs of drowsiness in individuals, especially in critical situations like driving, heavy machinery operation, or aircraft piloting. Hybrid Bi-directional Long... 详细信息
来源: 评论
SDM-SNN: Sparse distributed Memory Using Constant-Weight Fibonacci Code for Spiking neural network
SDM-SNN: Sparse Distributed Memory Using Constant-Weight Fib...
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2024 International VLSI Symposium on Technology, Systems and Applications, VLSI TSA 2024
作者: Zhou, Yu-Xuan Liu, Chih-Wei Institute of Electronics National Yang Ming Chiao Tung University Taiwan Industrial Technology Research Institute China
The long-term memory (LTM) is generally considered as the unlimited and permanent storage of information in the human brain. This concept has spurred numerous researches focusing on associative memory models, such as ... 详细信息
来源: 评论
A Deep Recurrent neural network Based Predictive Control Framework for Reliable distributed Stream Data processing  33
A Deep Recurrent Neural Network Based Predictive Control Fra...
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33rd IEEE International Parallel and distributed processing Symposium (IPDPS)
作者: Xu, Jielong Tang, Jian Xu, Zhiyuan Yin, Chengxiang Kwiat, Kevin Kamhoua, Charles Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA US Air Force Res Lab AFRL Wright Patterson AFB OH USA US Army Res Lab ARL Adelphi MD USA
In this paper, we present design, implementation and evaluation of a novel predictive control framework to enable reliable distributed stream data processing, which features a Deep Recurrent neural network (DRNN) mode... 详细信息
来源: 评论
distributed Heterogeneous Spiking neural network Simulator Using Sunway Accelerators
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Big Data Mining and Analytics 2024年 第4期7卷 1301-1320页
作者: Xuelei Li Zhichao Wang Yi Pan Jintao Meng Shengzhong Feng Yanjie Wei Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055Chinaand Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ)Shenzhen 518055China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Guangdong Institute of Intelligence Science and Technology Zhuhai 519031China
Spiking neural network(SNN)simulation is very important for studying brain function and validating the hypotheses for neuroscience,and it can also be used in artificial ***,GPU-based simulators have been developed to ... 详细信息
来源: 评论
MDLoader: A Hybrid Model-Driven Data Loader for distributed Graph neural network Training
MDLoader: A Hybrid Model-Driven Data Loader for Distributed ...
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2024 Workshops of the International Conference for High Performance Computing, networking, Storage and Analysis, SC Workshops 2024
作者: Bae, Jonghyun Choi, Jong Youl Pasini, Massimiliano Lupo Mehta, Kshitij Zhang, Pei Ibrahim, Khaled Z. Lawrence Berkeley National Laboratory United States Oak Ridge National Laboratory United States
Scalable data management is essential for processing large scientific dataset on HPC platforms for distributed deep learning. In-memory distributed storage is preferred for its speed, enabling rapid, random, and frequ... 详细信息
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Prediction and Evaluation Method of Modification Effect of Large-Scale DBD Insulation Materials Based on distributed Current Measurement and neural network Model  1st
Prediction and Evaluation Method of Modification Effect of L...
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1st Electrical Artificial Intelligence Conference, EAIC 2024
作者: Yizhuo, Wang Zhonlian, Li Long, Li Runhua, Li Xinglei, Cui Zhi, Fang School of Electrical Engineering and Control Science Nanjing Tech University Nanjing211816 China
Wide dielectric barrier discharge (DBD) has broad application prospects in the modification of insulating materials, but the aging of the electrode directly affects the modification effect in the application process. ... 详细信息
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DONNA: distributed Optimized neural network Allocation on CIM-Based Heterogeneous Accelerators  8
DONNA: Distributed Optimized Neural Network Allocation on CI...
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8th IEEE International Conference on Edge Computing and Communications, EDGE 2024
作者: Alshams, Mojtaba F. Smagulova, Kamilya S. Fahmy, Suhaib A. Fouda, Mohammed E. Eltawil, Ahmed M. King Abdullah University of Science and Technology CEMSE Division Thuwal23955 Saudi Arabia Rain Neuromorphics Inc. San FranciscoCA94110 United States
The continued development of neural network architectures continues to drive demand for computing power. While data center scaling continues, inference away from the cloud will increasingly rely on distributed inferen... 详细信息
来源: 评论
Sparsity-Aware Communication for distributed Graph neural network Training  24
Sparsity-Aware Communication for Distributed Graph Neural Ne...
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53rd International Conference on Parallel processing (ICPP)
作者: Mukhopadhyay, Ujjaini Tripathy, Alok Selvitopi, Oguz Yelick, Katherine Buluc, Aydin Univ Calif Berkeley Berkeley CA 94720 USA Lawrence Berkeley Nat Lab Berkeley CA USA
Graph neural networks (GNNs) are a computationally efficient method to learn embeddings and classifications on graph data. However, GNN training has low computational intensity, making communication costs the bottlene... 详细信息
来源: 评论