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Understanding the functional roles of financial institutions within interconnected markets is critical for effective supervision, systemic risk assessment, and resolution planning. We propose an interpretable role-based clustering approach…

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Cloud computing is quickly becoming pervasive in today's globally integrated networks. The cloud offers organizations opportunities to potentially deploy software and data solutions that are accessible through numerous mechanisms, in a…

Cryptography and Security · Computer Science 2013-06-12 George Grispos , William Bradley Glisson , Tim Storer

Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. For most applications, applying clustering is only appropriate when cluster structure is present. As such, the study of clusterability,…

Machine Learning · Statistics 2018-10-30 A. Adolfsson , M. Ackerman , N. C. Brownstein

Large-scale deployment of smart meters has made it possible to collect sufficient and high-resolution data of residential electric demand profiles. Clustering analysis of these profiles is important to further analyze and comment on…

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The financial sustainability of a generic supply chain is a complex problem, which can be addressed through detailed monitoring of financial operations deriving from stakeholder interrelationships and consequent analysis of these financial…

Clustering is a fundamental problem in machine learning and operations research. Therefore, given the fact that fairness considerations have become of paramount importance in algorithm design, fairness in clustering has received significant…

Machine Learning · Computer Science 2024-06-25 John Dickerson , Seyed A. Esmaeili , Jamie Morgenstern , Claire Jie Zhang

With the explosive growth of multi-source data, multi-view clustering has attracted great attention in recent years. Most existing multi-view methods operate in raw feature space and heavily depend on the quality of original feature…

Machine Learning · Computer Science 2022-05-20 Liang Liu , Peng Chen , Guangchun Luo , Zhao Kang , Yonggang Luo , Sanchu Han

Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying the discrete measurements/observations. Application of functional data clustering has appeared in many publications across…

Methodology · Statistics 2022-10-04 Mimi Zhang , Andrew Parnell

Cloud computing is a new computational paradigm that offers an innovative business model for organizations to adopt IT without upfront investment. Despite the potential gains achieved from the cloud computing, the model security is still…

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Clustering is one of the most universal approaches for understanding complex data. A pivotal aspect of clustering analysis is quantitatively comparing clusterings; clustering comparison is the basis for many tasks such as clustering…

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Multi-cloud concept has broaden the world of cloud computing and has become a buzzword today. The word Multi-cloud envisions utilization of services from multiple heterogeneous cloud providers via a single architecture at customer premises.…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-31 Deepika Saxena , Rishabh Gupta , Ashutosh Kumar Singh

This paper is a chapter in the forthcoming Handbook of Cluster Analysis, Hennig et al. (2015). For definitions of basic clustering methods and some further methodology, other chapters of the Handbook are referred to. To read this version of…

Methodology · Statistics 2015-03-09 Christian Hennig

Spectral clustering methods have gained widespread recognition for their effectiveness in clustering high-dimensional data. Among these techniques, constrained spectral clustering has emerged as a prominent approach, demonstrating enhanced…

Machine Learning · Computer Science 2024-04-05 Swarup Ranjan Behera , Vijaya V. Saradhi

Clustering is a widely-used data mining tool, which aims to discover partitions of similar items in data. We introduce a new clustering paradigm, \emph{accordant clustering}, which enables the discovery of (predefined) group level insights.…

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The energy industry needs to shift to a new paradigm from its classical model of energy generation, distribution, and management. This shift is necessary to handle digitization, increased renewable energy generation, and to achieve goals of…

Computers and Society · Computer Science 2019-12-02 Swati Megha , Joseph Lamptey , Hamza Salem , Manuel Mazzara

Conventional multi-view clustering seeks to partition data into respective groups based on the assumption that all views are fully observed. However, in practical applications, such as disease diagnosis, multimedia analysis, and…

Machine Learning · Computer Science 2022-08-18 Jie Wen , Zheng Zhang , Lunke Fei , Bob Zhang , Yong Xu , Zhao Zhang , Jinxing Li

Fintech companies have been facing challenges from fraudulent behavior for a long time. Fraud rate in Chinese P2P financial market could go as high as 10%. It is crucial to collect sufficient information of the user as input to the…

Other Computer Science · Computer Science 2019-10-07 Hao Wang , Zonghu Wang , Bin Zhang , Jun Zhou

Cloud computing is a web-based utility model that is becoming popular every day with the emergence of 4th Industrial Revolution, therefore, cybercrimes that affect web-based systems are also relevant to cloud computing. In order to conduct…

Cryptography and Security · Computer Science 2023-03-14 Sayada Sonia Akter , Mohammad Shahriar Rahman

Number of connected devices is steadily increasing and these devices continuously generate data streams. Real-time processing of data streams is arousing interest despite many challenges. Clustering is one of the most suitable methods for…

Machine Learning · Computer Science 2020-07-22 Alaettin Zubaroğlu , Volkan Atalay

Today cloud computing has become as a new concept for hosting and delivering different services over the Internet for big data solutions. Cloud computing is attractive to different business owners of both small and enterprise as it…

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