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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"
7123 条 记 录,以下是4931-4940 订阅
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OpenStack Network Acceleration Scheme for datacenter intelligent Applications
OpenStack Network Acceleration Scheme for Datacenter Intelli...
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IEEE international conference on Cloud Computing, CLOUD
作者: Linh Phan Kaikai Liu Computer Engineering Department San Jose State University (SJSU) San Jose CA USA
Cloud virtualization and multi-tenant networking provide Infrastructure as a Service (IaaS) providers a new and innovative way to offer on-demand services to their customers, such as easy provisioning of new applicati... 详细信息
来源: 评论
Automatically Design Distance Functions for Graph-based Semi-Supervised learning  16
Automatically Design Distance Functions for Graph-based Semi...
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16th IEEE international conference on Trust, Security and Privacy in Computing and Communications / the 11th IEEE international conference on Big data Science and engineering / the 14th IEEE international conference on Embedded Software and Systems
作者: Miquilini, Patricia Rossi, Rafael G. Quiles, Marcos G. de Melo, Vinicius V. Basgalupp, Marcio P. Univ Fed Sao Paulo Inst Sci & Technol Sao Paulo Brazil Univ Fed Mato Grosso do Sul Campo Grande MS Brazil
Automatic data classification is often performed by supervised learning algorithms, producing a model to classify new instances. Reflecting that labeled instances are expensive, semi supervised learning (SSL) methods ... 详细信息
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Intermediate data Caching Optimization for Multi-Stage and Parallel Big data Frameworks
Intermediate Data Caching Optimization for Multi-Stage and P...
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IEEE international conference on Cloud Computing, CLOUD
作者: Zhengyu Yang Danlin Jia Stratis Ioannidis Ningfang Mi Bo Sheng Dept. of Electrical & Computer Engineering Northeastern University Boston MA Dept. of Computer Science University of Massachusetts Boston Boston MA
In the era of big data and cloud computing, large amounts of data are generated from user applications and need to be processed in the datacenter. data-parallel computing frameworks, such as Apache Spark, are widely u... 详细信息
来源: 评论
Large-scale multi-label ensemble learning on Spark  16
Large-scale multi-label ensemble learning on Spark
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16th IEEE international conference on Trust, Security and Privacy in Computing and Communications / the 11th IEEE international conference on Big data Science and engineering / the 14th IEEE international conference on Embedded Software and Systems
作者: Gonzalez-Lopez, Jorge Cano, Alberto Ventura, Sebastian Virginia Commonwealth Univ Dept Comp Sci Richmond VA 23284 USA Univ Cordoba Dept Comp Sci Cordoba Spain
Multi-label learning is a challenging problem which has received growing attention in the research community over the last years. Hence, there is a growing demand of effective and scalable multi-label learning methods... 详细信息
来源: 评论
Software Effort Estimation using Machine learning Techniques  7
Software Effort Estimation using Machine Learning Techniques
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7th international conference on Cloud Computing, data Science and engineering (Confluence)
作者: Monika Sangwan, Om Prakash Guru Jambheshwar Univ Sci & Technol Dept Comp Sci & Engn Hisar Haryana India
Effort Estimation is a very important activity for planning and scheduling of software project life cycle in order to deliver the product on time and within budget. Machine learning techniques are proving very useful ... 详细信息
来源: 评论
11th Curtin University Technology, Science and engineering (CUTSE) international conference
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IOP conference Series: Materials Science and engineering 2019年 第1期495卷
Preface the 11th Curtin University Technology, Science and engineering (CUTSE) international conference was held on 26-28 November 2018 at Curtin University Malaysia at Miri, Sarawak, Malaysia. this year's confere...
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Machine learning Approach to Task Ranking  14
Machine Learning Approach to Task Ranking
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14th international Symposium on Pervasive Systems, Algorithms and Networks (I-SPAN) / 11th international conference on Frontier of Computer Science and Technology (FCST) / 3rd international Symposium of Creative Computing (ISCC)
作者: Ricky, Michael Yoseph Hendric, Spits Warnars Harco Leslie Budiharto, Widodo Abbas, Bahtiar Saleh Bina Nusantara Univ Jakarta Indonesia
there are variety of methods and algorithms that can be used to overcome the ranking problem. Task ranking is one of the problems that can be solved by using a machine learning algorithm ranking problem. this work foc... 详细信息
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Sequential and Unsupervised Document Authorial Clustering Based on Hidden Markov Model  16
Sequential and Unsupervised Document Authorial Clustering Ba...
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16th IEEE international conference on Trust, Security and Privacy in Computing and Communications / the 11th IEEE international conference on Big data Science and engineering / the 14th IEEE international conference on Embedded Software and Systems
作者: Aldebei, Khaled Farhood, Helia Jia, Wenjing Nanda, Priyadarsi He, Xiangjian Univ Technol Sydney Global Big Data Technol Ctr Sydney NSW Australia Minjiang Univ Fujian Prov Key Lab Informat Proc & Intelligent C Fuzhou 350121 Fujian Peoples R China
Document clustering groups documents of certain similar characteristics in one cluster. Document clustering has shown advantages on organization, retrieval, navigation and summarization of a huge amount of text docume... 详细信息
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Distributed cooperative hierarchical control for DC microgrid
Distributed cooperative hierarchical control for DC microgri...
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the 11th IET international conference on Advances in Power System Control, Operation and Management (APSCOM 2018)
作者: Chunyuan Guo Li Qiu Bo Zhang Jianping Yuan College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Intelligent Operation Laboratory Research Institute of Northwestern Polytechnical University in Shenzhen Shenzhen China
this paper proposes a distributed cooperative hierarchical control scheme for DC microgrid based on consensus algorithm. the control architecture includes primary control, secondary control and tertiary control, which...
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AutoLearn - automated Feature Generation and Selection  17
AutoLearn - Automated Feature Generation and Selection
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17th IEEE international conference on data Mining (ICDMW)
作者: Kaul, Ambika Maheshwary, Saket Pudi, Vikram Int Inst Informat Technol Kohli Ctr Intelligent Syst Data Sci & Analyt Ctr Hyderabad Andhra Pradesh India
In recent years, the importance of feature engineering has been confirmed by the exceptional performance of deep learning techniques, that automate this task for some applications. For others, feature engineering requ... 详细信息
来源: 评论