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检索条件"机构=Key Lab of Intelligent Computing based Big Data of Zhejiang Province"
44 条 记 录,以下是1-10 订阅
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LeapGNN: Accelerating Distributed GNN Training Leveraging Feature-Centric Model Migration  23
LeapGNN: Accelerating Distributed GNN Training Leveraging Fe...
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23rd USENIX Conference on File and Storage Technologies, FAST 2025
作者: Chen, Weijian He, Shuibing Qu, Haoyang Zhang, Xuechen The State Key Laboratory of Blockchain and Data Security Zhejiang University China Zhejiang Lab China Institute of Blockchain and Data Security China Zhejiang Key Laboratory of Big Data Intelligent Computing China Washington State University Vancouver United States
Distributed training of graph neural networks (GNNs) has become a crucial technique for processing large graphs. Prevalent GNN frameworks are model-centric, necessitating the transfer of massive graph vertex features ... 详细信息
来源: 评论
GoPIM: GCN-Oriented Pipeline Optimization for PIM Accelerators  31
GoPIM: GCN-Oriented Pipeline Optimization for PIM Accelerato...
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31st IEEE International Symposium on High Performance Computer Architecture, HPCA 2025
作者: Yang, Siling He, Shuibing Wang, Wenjiong Yin, Yanlong Wu, Tong Chen, Weijian Zhang, Xuechen Sun, Xian-He Feng, Dan The State Key Laboratory of Blockchain and Data Security Zhejiang University China Zhejiang Lab China Institute of Blockchain and Data Security China Zhejiang Key Laboratory of Big Data Intelligent Computing China Washington State University Vancouver United States Illinois Institute of Technology United States Huazhong University of Science and Technology China Wuhan National Laboratory for Optoelectronics China
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
LeapGNN: accelerating distributed GNN training leveraging feature-centric model migration  25
LeapGNN: accelerating distributed GNN training leveraging fe...
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Proceedings of the 23rd USENIX Conference on File and Storage Technologies
作者: Weijian Chen Shuibing He Haoyang Qu Xuechen Zhang The State Key Laboratory of Blockchain and Data Security Zhejiang University and Zhejiang Lab and Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security and Zhejiang Key Laboratory of Big Data Intelligent Computing Washington State University Vancouver
Distributed training of graph neural networks (GNNs) has become a crucial technique for processing large graphs. Prevalent GNN frameworks are model-centric, necessitating the transfer of massive graph vertex features ...
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
Incomplete data management: a survey
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Frontiers of Computer Science 2018年 第1期12卷 4-25页
作者: Xiaoye MIAO Yunjun GAO Su GUO Wanqi LIU College of Computer Science Zhejiang University Hangzhou 310027 China The Key Lab of Big Data Intelligent Computing of Zhejiang Province Zhejiang University Hangzhou 310027 China
Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query in... 详细信息
来源: 评论
SMILE: A Cost-Effective System for Serving Massive Pretrained Language Models in the Cloud  23
SMILE: A Cost-Effective System for Serving Massive Pretraine...
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2023 ACM/SIGMOD International Conference on Management of data, SIGMOD 2023
作者: Wang, Jue Chen, Ke Shou, Lidan Jiang, Dawei Chen, Gang Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang University Hangzhou China
Deep learning models, particularly pre-trained language models (PLMs), have become increasingly important for a variety of applications that require text/language processing. However, these models are resource-intensi... 详细信息
来源: 评论
Dual Enhancement for Multi-label Learning with Missing labels  21
Dual Enhancement for Multi-Label Learning with Missing Label...
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4th International Conference on Machine Learning and Machine Intelligence, MLMI 2021
作者: Liu, Shengyuan Wang, Haobo Hu, Tianlei Chen, Ke Key Lab of Intelligent Computing Based Big Data of Zhejiang Province College of Computer Science and Technology Zhejiang University China
The goal of multi-label learning with missing labels (MLML) is assigning each testing instance multiple labels given training instances that have a partial set of labels. The most challenging issue is to complete the ... 详细信息
来源: 评论
Complementary label Queries for Efficient Active Learning  23
Complementary Label Queries for Efficient Active Learning
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6th International Conference on Image and Graphics Processing, ICIGP 2023
作者: Liu, Shengyuan Hu, Tianlei Chen, Ke Mao, Yunqing Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang University China Co. Ltd. China
Many active learning methods are based on the assumption that a learner simply asks for the true labels of some training data from annotators. Unfortunately, it is expensive to exactly annotate instances in real-world... 详细信息
来源: 评论
Complex integrity constraint discovery: measuring trust in modern intelligent railroad systems
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Journal of zhejiang University-Science A(Applied Physics & Engineering) 2022年 第10期23卷 832-837页
作者: Wen-tao HU Da-wei JIANG Sai WU Ke CHEN Gang CHEN Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang UniversityHangzhou 310027China
1Introduction data are at the heart of intelligent rail systems in the high-speed transportation sector(Zhou et al.,2020;Ho et al.,2021;Hu et al.,2021;Chen et al.,2022).The core of modern intelligent railroad systems ... 详细信息
来源: 评论
Collaboration based multi-label propagation for fraud detection  29
Collaboration based multi-label propagation for fraud detect...
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29th International Joint Conference on Artificial Intelligence, IJCAI 2020
作者: Wang, Haobo Li, Zhao Huang, Jiaming Hui, Pengrui Liu, Weiwei Hu, Tianlei Chen, Gang Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang University China Alibaba Group Hangzhou China School of Computer Science Wuhan University China
Detecting fraud users, who fraudulently promote certain target items, is a challenging issue faced by e-commerce platforms. Generally, many fraud users have different spam behaviors simultaneously, e.g. spam transacti... 详细信息
来源: 评论