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检索条件"机构=Key Laboratory of Computer Vision and Machine Learning"
337 条 记 录,以下是131-140 订阅
排序:
Multi-Modal Perception Attention Network with Self-Supervised learning for Audio-Visual Speaker Tracking
arXiv
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arXiv 2021年
作者: Li, Yidi Liu, Hong Tang, Hao Key Laboratory of Machine Perception Peking University Shenzhen Graduate School China Computer Vision Lab ETH Zurich Switzerland
Multi-modal fusion is proven to be an effective method to improve the accuracy and robustness of speaker tracking, especially in complex scenarios. However, how to combine the heterogeneous information and exploit the... 详细信息
来源: 评论
Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks
arXiv
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arXiv 2022年
作者: Xu, Yonghao Yu, Weikang Ghamisi, Pedram Kopp, Michael Hochreiter, Sepp Vienna1030 Austria Computer Vision Laboratory Department of Electrical Engineering Linköping University Linköping58183 Sweden Helmholtz-Zentrum Dresden-Rossendorf Helmholtz Institute Freiberg for Resource Technology Machine Learning Group Freiberg09599 Germany ELLIS Unit Linz and LIT AI Lab Institute for Machine Learning Johannes Kepler University Linz4040 Austria
The synthesis of high-resolution remote sensing images based on text descriptions has great potential in many practical application scenarios. Although deep neural networks have achieved great success in many importan... 详细信息
来源: 评论
HQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidance
arXiv
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arXiv 2023年
作者: He, Chunming Li, Kai Xu, Guoxia Yan, Jiangpeng Tang, Longxiang Zhang, Yulun Li, Xiu Wang, Yaowei Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Machine Learning Department NEC Laboratories America Inc. NJ08540 United States Department of Computer Science Norwegian University of Science and Technology Gjovik2815 Norway The Computer Vision Lab ETH Zürich Zürich8092 Switzerland Peng Cheng Laboratory Shenzhen518066 China
Unpaired Medical Image Enhancement (UMIE) aims to transform a low-quality (LQ) medical image into a high-quality (HQ) one without relying on paired images for training. While most existing approaches are based on Pix2... 详细信息
来源: 评论
BGTplanner: Maximizing Training Accuracy for Differentially Private Federated Recommenders via Strategic Privacy Budget Allocation
arXiv
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arXiv 2024年
作者: Zhang, Xianzhi Zhou, Yipeng Hu, Miao Wu, Di Liao, Pengshan Guizani, Mohsen Sheng, Michael The School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China The Department of Computing Faculty of Science and Engineering Macquarie University Sydney Australia The Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates
To mitigate the rising concern about privacy leakage, the federated recommender (FR) paradigm emerges, in which decentralized clients co-train the recommendation model without exposing their raw user-item rating data.... 详细信息
来源: 评论
Cross-Store Next-Basket Recommendation
Cross-Store Next-Basket Recommendation
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IEEE International Conference on Data Mining (ICDM)
作者: Liang-Chen Ma Ya Li Zi-Feng Mai Fei-Yao Liang Chang-Dong Wang Min Chen Mohsen Guizani School of Computer Science and Engineering Sun Yat-sen University Guangzhou China School of Electronics and Information Guangdong Polytechnic Normal University Guangzhou China Guangdong Provincial Key Laboratory of Intellectual Property and Big Data Guangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE
Next-basket recommendation (NBR) infers a set of items that a user will interact with in the next basket. Existing methods often struggle with the data sparsity problem, particularly when the number of baskets is sign... 详细信息
来源: 评论
RecCoder: Reformulating Sequential Recommendation as Large Language Model-Based Code Completion
RecCoder: Reformulating Sequential Recommendation as Large L...
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IEEE International Conference on Data Mining (ICDM)
作者: Kai-Huang Lai Wu-Dong Xi Xing-Xing Xing Wei Wan Chang-Dong Wang Min Chen Mohsen Guizani School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Contribution during internship at NetEase Games UX Center NetEase Games Guangzhou China Guangdong Provincial Key Laboratory of Intellectual Property and Big Data Guangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE
In the evolving landscape of sequential recommendation systems, the application of Large Language Models (LLMs) is increasingly prominent. However, current attempts typically utilize general-purpose LLMs, which presen... 详细信息
来源: 评论
Contrastive learning for Adapting Language Model to Sequential Recommendation
Contrastive Learning for Adapting Language Model to Sequenti...
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IEEE International Conference on Data Mining (ICDM)
作者: Fei-Yao Liang Wu-Dong Xi Xing-Xing Xing Wei Wan Chang-Dong Wang Min Chen Mohsen Guizani School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Contribution during internship at NetEase Games UX Center NetEase Games Guangzhou China Guangdong Provincial Key Laboratory of Intellectual Property and Big Data Guangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE
With the explosive growth of information, recommendation systems have emerged to alleviate the problem of information overload. In order to improve the performance of recommendation systems, many existing methods intr... 详细信息
来源: 评论
Dynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly Detection
arXiv
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arXiv 2023年
作者: Zhang, Chen Li, Guorong Qi, Yuankai Ye, Hanhua Qing, Laiyun Yang, Ming-Hsuan Huang, Qingming State Key Laboratory of Information Security Institute of Information Engineering CAS China School of Cyber Security University of Chinese Academy of Sciences China School of Computer Science and Technology University of Chinese Academy of Sciences China Australian Institute for Machine Learning The University of Adelaide Australia University of California Merced United States Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS China
The goal of weakly supervised video anomaly detection is to learn a detection model using only video-level labeled data. However, prior studies typically divide videos into fixed-length segments without considering th... 详细信息
来源: 评论
GSLB: The Graph Structure learning Benchmark  37
GSLB: The Graph Structure Learning Benchmark
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37th Conference on Neural Information Processing Systems, NeurIPS 2023
作者: Li, Zhixun Wang, Liang Sun, Xin Luo, Yifan Zhu, Yanqiao Chen, Dingshuo Luo, Yingtao Zhou, Xiangxin Liu, Qiang Wu, Shu Yu, Jeffrey Xu Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Department of Automation University of Science and Technology of China China School of Cyberspace Security Beijing University of Posts and Telecommunications China Department of Computer Science University of California Los Angeles United States Heinz College of Information Systems and Public Policy Machine Learning Department School of Computer Science Carnegie Mellon University United States
Graph Structure learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation graph structure simultaneously. Despit... 详细信息
来源: 评论
GeneDroid Fuzz: An Android Intent Fuzzing Method Based on Gene Mutation
GeneDroid Fuzz: An Android Intent Fuzzing Method Based on Ge...
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IEEE Conference on Global Communications (GLOBECOM)
作者: Runfeng Lu Yuzhu Sun Haofeng Sun Xiao Fu Bin Luo Xiaojiang Du Jin Shi Nadjib Aitsaadi Mohsen Guizani State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ USA School of Information Management Nanjing University Nanjing China DAVID UVSQ Université Paris-Saclay France Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi UAE
With the rapid expansion of mobile internet usage, the prevalence of the Android operating system on smartphones is steadily growing. However, improper utilization of the Intent mechanism within Android applications c... 详细信息
来源: 评论