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检索条件"机构=Data Science Program Computer Science Department"
24664 条 记 录,以下是4701-4710 订阅
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A Hybrid Deep Learning-Based Unsupervised Anomaly Detection in High Dimensional data
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computers, Materials & Continua 2022年 第3期70卷 5363-5381页
作者: Amgad Muneer Shakirah Mohd Taib Suliman Mohamed Fati Abdullateef O.Balogun Izzatdin Abdul Aziz Department of Computer and Information Sciences Universiti Teknologi PETRONASSeri Iskandar32160Malaysia Centre for Research in Data Science(CERDAS) Universiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Information Systems Department Prince Sultan UniversityRiyadh11586Saudi Arabia
Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world *** issues in this field still unsolved,so several modern anomaly detection methods struggle to mainta... 详细信息
来源: 评论
Improving Audience Ratings Prediction of Japanese TV Dramas Using Knowledge-Based Embeddings  23
Improving Audience Ratings Prediction of Japanese TV Dramas ...
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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024
作者: Bonnell, Jerry Wuchty, Stefan Ogihara, Mitsunori Frost Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States University of Miami Department of Computer Science Coral GablesFL33146 United States
Accurate prediction of television (TV) audience ratings is a crucial technology for advertisers and broadcast-ers, which influences advertising costs and indicates program popularity. As for Japanese TV dramas, previo... 详细信息
来源: 评论
Utilizing the simple graph convolutional neural network as a model for simulating influence spread in networks
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Computational Social Networks 2021年 第1期8卷 1-17页
作者: Mantzaris, Alexander V. Chiodini, Douglas Ricketson, Kyle Department of Statistics and Data Science University of Central Florida (UCF) 4000 Central Florida Blvd Orlando 32816 United States Department of Computer Science University of Central Florida (UCF) 4000 Central Florida Blvd Orlando 32816 United States
The ability for people and organizations to connect in the digital age has allowed the growth of networks that cover an increasing proportion of human interactions. The research community investigating networks asks a... 详细信息
来源: 评论
Real-Time Intelligent Information Protection Using AI and Machine Learning Model  8
Real-Time Intelligent Information Protection Using AI and Ma...
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8th IEEE International Conference on science, Technology, Engineering and Mathematics, ICONSTEM 2023
作者: Anusha, P. Beatrice Dorothy, A. Kamalraj, N. Pundir, Sumit Verma, Shanti Jakka, Geethamanikanta R.M.K. Engineering College Department of Electronics and Communication Engineering Tamilnadu India Department of Data Science Tiruchirappalli620002 India Suguna College of Arts and Science Department of Computer Science Tamilnadu Coimbatore India Graphic Era Deemed to Be University Department of Computer Science Engineering Uttrakhand Dehradun India Lj University Department of Computer Applications Gujarat Ahmedabad India University of the Cumberlands Department of Information Technology FremontCA United States
Machine learning (ML) and Artificial intelligence (AI) are crucial components in the field of information security due to their capacity for rapid analysis of millions of events and identification of a wide variety of... 详细信息
来源: 评论
Smart Agriculture System  4th
Smart Agriculture System
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4th International Conference on computer Vision, High-Performance Computing, Smart Devices, and Networks, CHSN 2023
作者: Kanaujia, Vishal Kumar Sah, Chitranjan Prasad Computer Science and Engineering-Data Science Department ABES Engineering College Uttar Pradesh Ghaziabad India School of Engineering and Technology Noida International University Uttar Pradesh Greater Noida India
Agriculture stands as a linchpin for national prosperity, especially in regions blessed with abundant water and fertile soil, capable of yielding a diverse range of food products crucial for human sustenance. However,... 详细信息
来源: 评论
NEARLY MINIMAX OPTIMAL OFFLINE REINFORCEMENT LEARNING WITH LINEAR FUNCTION APPROXIMATION: SINGLE-AGENT MDP AND MARKOV GAME  11
NEARLY MINIMAX OPTIMAL OFFLINE REINFORCEMENT LEARNING WITH L...
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11th International Conference on Learning Representations, ICLR 2023
作者: Xiong, Wei Zhong, Han Shi, Chengshuai Shen, Cong Wang, Liwei Zhang, Tong Department of Mathematics The Hong Kong University of Science and Technology Hong Kong Center for Data Science Peking University China Department of Electrical and Computer Engineering University of Virginia United States National Key Laboratory of General Artificial Intelligence Peking University China School of Intelligence Science and Technology Peking University China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong
Offline reinforcement learning (RL) aims at learning an optimal strategy using a pre-collected dataset without further interactions with the environment. While various algorithms have been proposed for offline RL in t... 详细信息
来源: 评论
Exploring the Effect of Activation Function on Transformer Model Performance for Official Announcement Translator from Indonesian to Sundanese Languages
Exploring the Effect of Activation Function on Transformer M...
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2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023
作者: Wijanarko, Bambang Dwi Fitria Murad, Dina Heryadi, Yaya Tho, Cuk Hashimoto, Kiyota BINUS Online Learning Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket Campus Phuket83120 Thailand
Automated language translation involving low-resource language has gained wide interest from many research communities in the past decade. One lesson learned from the past COVID-19 pandemic, particularly in Indonesia,... 详细信息
来源: 评论
The collaborative strategy of multiple USVs with deep reinforcement learning method  18
The collaborative strategy of multiple USVs with deep reinfo...
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18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2019
作者: Wu, Xing Zhong, Mingyu Feng, Guofei Xie, Shaorong Guo, Yike School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai China Department of Computing Imperial College London London United Kingdom
The unmanned surface vehicle (USV) has been widely used to accomplish tasks that cannot be completed by ships with human drivers on certain sea areas. It is not only necessary but essential to obtain a robust strategy... 详细信息
来源: 评论
Inductive Relation Prediction by Disentangled Subgraph Structure
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Tsinghua science and Technology 2024年 第5期29卷 1566-1579页
作者: Guiduo Duan Rui Guo Wenlong Luo Guangchun Luo Tianxi Huang Laboratory of Intelligent Collaborative Computing University of Electronic Science and Technology of ChinaChengdu 611731Chinaand also with Trusted Cloud Computing and Big Data Key Laboratory of Sichuan ProvinceChengdu 611731China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Hangzhou NetEase Cloud Music Technology Co. Ltd.Hangzhou 310052China Department of Fundamental Courses Chengdu Textile CollegeChengdu 611700China
Currently,most existing inductive relation prediction approaches are based on subgraph structures,with subgraph features extracted using graph neural networks to predict ***,subgraphs may contain disconnected regions,... 详细信息
来源: 评论
Federated Model Heterogeneous Matryoshka Representation Learning  38
Federated Model Heterogeneous Matryoshka Representation Lear...
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Yi, Liping Yu, Han Ren, Chao Wang, Gang Liu, Xiaoguang Li, Xiaoxiao College of Computer Science TMCC SysNet DISSec GTIISC Nankai University China College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering The University of British Columbia Canada Vector Institute Canada
Model heterogeneous federated learning (MHeteroFL) enables FL clients to collaboratively train models with heterogeneous structures in a distributed fashion. However, existing MHeteroFL methods rely on training loss t...
来源: 评论