Towards optimal k-prototype discovery,k-means-like algorithms give us inspirations of central samples collection,yet the unstable seed samples selection,the hypothesis of a circle-like pattern,and the unknown K are st...
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Towards optimal k-prototype discovery,k-means-like algorithms give us inspirations of central samples collection,yet the unstable seed samples selection,the hypothesis of a circle-like pattern,and the unknown K are still challenges,particularly for non-predetermined data *** propose an adaptive k-prototype clustering method(kProtoClust)which launches cluster exploration with a sketchy division of K clusters and finds evidence for splitting and *** behalf of a group of data samples,support vectors and outliers from the perspective of support vector data description are not the appropriate candidates for prototypes,while inner samples become the first candidates for instability reduction of *** from the representation of samples in traditional,we extend sample selection by encouraging fictitious samples to emphasize the representativeness of *** get out of the circle-like pattern limitation,we introduce a convex decomposition-based strategy of one-cluster-multiple-prototypes in which convex hulls of varying sizes are prototypes,and accurate connection analysis makes the support of arbitrary cluster shapes *** by geometry,the three presented strategies make kProtoClust bypassing the K dependence well with the global and local position relationship analysis for data *** results on twelve datasets of irregular cluster shape or high dimension suggest that kProtoClust handles arbitrary cluster shapes with prominent accuracy even without the prior knowledge K.
In recent years, hypergraph representation learning (HGRL) has become a focus of academic research, which aims to extract high-order topological patterns and attributes from hypergraph into low-dimensional representat...
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This article explores the plagiarism problem of ChatGPT in the education field in detail and proposes a study to evaluate its plagiarism effect. First, it introduces ChatGPT as an important innovation based on GPT tec...
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Reliability monitoring of financial health requires strong control mechanisms, and the residual chart is an invaluable instrument to perform it. One of the key problems statisticians face while modeling is the problem...
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We explore the use of the well established lexical resource and theory of the Berkeley FrameNet project to support the creation of a domain-specific knowledge graph in the financial domain, more precisely from financi...
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In this paper,we prove the conjectured order lower bound for the k-th moment of central values of quadratic twisted self-dual GL(3)L-functions for all k≥1,based on our recent work on the twisted first moment of centr...
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In this paper,we prove the conjectured order lower bound for the k-th moment of central values of quadratic twisted self-dual GL(3)L-functions for all k≥1,based on our recent work on the twisted first moment of central values in this family of L-functions.
Machine learning models trained on human language, also known as Natural Language Processing (NLP) models, are susceptible to manipulation. These attacks, called NLP attacks, work by subtly altering the input text. Th...
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This study examines the dynamics of data management and knowledge flow in the political data ecosystem through the lens of the Knowledge Pyramid. We used open-government electoral documents and polling data for granul...
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Polycystic Ovary Syndrome (PCOS) is a common reproductive and metabolic disorder characterized by an increased number of ovarian follicles. Accurate diagnosis of PCOS requires detailed ultrasound imaging to assess fol...
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Recent studies in Multimodal Machine Translation (MMT) have explored the use of visual information in a multimodal setting to analyze its redundancy with textual information. The aim of this work is to develop a more ...
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