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检索条件"机构=Zhejiang Key Laboratory of Big Data Intelligent Computing"
724 条 记 录,以下是111-120 订阅
排序:
TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering  38
TFGDA: Exploring Topology and Feature Alignment in Semi-supe...
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Dan, Jun Liu, Weiming Xie, Chunfeng Yu, Hua Dong, Shunjie Tan, Yanchao Zhejiang University China Queen Mary University of London United Kingdom Dalian University of Technology China Shanghai Jiao Tong University China Fuzhou University China Engineering Research Center of Big Data Intelligence Ministry of Education China Fujian Key Laboratory of Network Computing and Intelligent Information Processing China
Semi-supervised graph domain adaptation, as a branch of graph transfer learning, aims to annotate unlabeled target graph nodes by utilizing transferable knowledge learned from a label-scarce source graph. However, mos...
来源: 评论
Research on WNN Greenhouse Temperature Prediction Method Based on GA
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Phyton-International Journal of Experimental Botany 2022年 第10期91卷 2283-2296页
作者: Wenbin Dai Lina Wang Binrui Wang Xiaohong Cui Xue Li College of Mechanical and Electronic Engineering China Jiliang UniversityHangzhou310018China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang UniversityHangzhou310018China
Temperature in agricultural production has a direct impact on the growth of *** emergence of greenhouses has improved the impact of the original unpredictable changes in temperature,but the temperature modeling of g... 详细信息
来源: 评论
A Model robustness optimization method based on adversarial sample detection  5
A Model robustness optimization method based on adversarial ...
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5th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2022
作者: Sun, Jiaze Long, Siyuan Ma, Xianyan Tang, Yanmei Xi'an University of Posts and Telecommunications Shaanxi Provincial Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'an710121 China Xi'an University of Posts and Telecommunications Xi'an710121 China
Deep neural networks are extremely vulnerable due to the existence of adversarial samples. It is a challenging problem to optimize the robustness of the model to protect deep neural networks from the threat of adversa... 详细信息
来源: 评论
GoPIM: GCN-Oriented Pipeline Optimization for PIM Accelerators
GoPIM: GCN-Oriented Pipeline Optimization for PIM Accelerato...
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IEEE Symposium on High-Performance Computer Architecture
作者: Siling Yang Shuibing He Wenjiong Wang Yanlong Yin Tong Wu Weijian Chen Xuechen Zhang Xian-He Sun Dan Feng The State Key Laboratory of Blockchain and Data Security Zhejiang University Zhejiang Lab Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security Zhejiang Key Laboratory of Big Data Intelligent Computing Washington State University Vancouver Illinois Institute of Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics
Graph convolutional networks (GCNs) are popular for a variety of graph learning tasks. ReRAM-based processing-in-memory (PIM) accelerators are promising to expedite GCN training owing to their in-situ computing capabi... 详细信息
来源: 评论
Research on key technologies of edge cache in virtual data space across WAN
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Frontiers of Computer Science 2023年 第1期17卷 15-34页
作者: Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China
The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputi... 详细信息
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IMPACT: Importance-Informed Prefetching and Caching for I/O-Bound DNN Training
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IEEE Transactions on Computers 2025年
作者: Chen, Weijian He, Shuibing Zhang, Ruidong Zhang, Xuechen Chen, Ping Yang, Siling Qu, Haoyang Zhan, Xuan Zhejiang University State Key Laboratory of Blockchain and Data Security China Institute of Blockchain and Data Security Hangzhou China Zhejiang Key Laboratory of Big Data Intelligent Computing China Washington State University Vancouver School of Engineering and Computer Science VancouverWA98686 United States
Fetching large amounts of DNN training data from storage systems causes high I/O latency and GPU stalls. Importance sampling can reduce data processing on GPUs while maintaining model accuracy, but current frameworks ... 详细信息
来源: 评论
How Do LLMs Acquire New Knowledge? A Knowledge Circuits Perspective on Continual Pre-Training
arXiv
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arXiv 2025年
作者: Ou, Yixin Yao, Yunzhi Zhang, Ningyu Jin, Hui Sun, Jiacheng Deng, Shumin Li, Zhenguo Chen, Huajun Zhejiang University China Huawei Noah’s Ark Lab Canada National University of Singapore NUS-NCS Joint Lab Singapore Zhejiang Key Laboratory of Big Data Intelligent Computing China
Despite exceptional capabilities in knowledge-intensive tasks, Large Language Models (LLMs) face a critical gap in understanding how they internalize new knowledge, particularly how to structurally embed acquired know... 详细信息
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MLLM CAN SEE? DYNAMIC CORRECTION DECODING FOR HALLUCINATION MITIGATION
arXiv
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arXiv 2024年
作者: Wang, Chenxi Chen, Xiang Zhang, Ningyu Tian, Bozhong Xu, Haoming Deng, Shumin Chen, Huajun Zhejiang University China Nanjing University of Aeronautics and Astronautics China National University of Singapore NUS-NCS Joint Lab Singapore Zhejiang Key Laboratory of Big Data Intelligent Computing China
Multimodal Large Language Models (MLLMs) frequently exhibit hallucination phenomena, but the underlying reasons remain poorly understood. In this paper, we present an empirical analysis and find that, although MLLMs i... 详细信息
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State-of-Charge Estimation of Lithium Battery Based on Deep Residual Shrinkage Networks and a Variant Long Short Term Memory Neural Network
State-of-Charge Estimation of Lithium Battery Based on Deep ...
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第35届中国控制与决策会议
作者: Penghua Li Yihui Zhang Key Laboratory of Intelligent Computing for Big Data College of Automation Chongqing University of Posts and Telecommunications
Accurate state-of-charge(SOC) estimation,which is critical to ensuring the safe and reliable operation of battery management systems in electric vehicles,is still a challenging task due to sophisticated battery dynami... 详细信息
来源: 评论
A Self-decoupled Interpretable Prediction Framework for Highly-Variable Cloud Workloads  28th
A Self-decoupled Interpretable Prediction Framework for Hig...
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28th International Conference on database Systems for Advanced Applications, DASFAA 2023
作者: Wang, Bingchao Shi, Xiaoyu Shang, Mingsheng Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China Chongqing School University of Chinese Academy of Sciences Chongqing400714 China Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China
Cloud workloads prediction plays a crucial role in the various tasks of cloud computing, such as resource scheduling, performance optimization, cost management, etc. However, current time series prediction methods suf... 详细信息
来源: 评论