Results 41 to 50 of about 1,566,699 (318)
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010 Object matching is a fundamental operation in data analysis. It typically requires the definition of a similarity measure between the classes of objects to be matched. Instead, we develop an approach which is able to perform matching by requiring a similarity measure only within each of the classes. This is achieved by maximizing the dependency between
Novi, Quadrianto +3 more
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On the Kernel of a Polynomial of Scalar Derivations
Mathematics, 2020 In this paper, by using a vector variable, the procedure of characteristic systems allows us to describe the kernel of a polynomial of scalar derivations by solving Cauchy Problems for the corresponding system of ODEs. Moreover, a gradient representation
Savin Treanţă
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Hierarchical Kernel And Sub-Kernels [PDF]
American Review of Mathematics and Statistics, 2017 This paper shows the theoretical development of hierarchy by kernels and an algorithm used to obtain an interesting class or partition from a hierarchy. Also shown is the theorem about the Kernels Optimal Criterion and how it is expressed as a function of the masses of the points of the vector space and product scale points, the inertia of the cloud ...
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Analysis in Theory and Applications, 2009 Summary: This paper is an extension of earlier papers [\textit{R. Schaback}, in: New developments in approximation theory. 2nd international Dortmund meeting (IDoMAT) '98, Germany, February 23-27, 1998. Basel: Birkhäuser. ISNM, Int. Ser. Numer. Math. 132, 255--282 (1999; Zbl 0944.46017); J. Comput. Appl. Math.
Mouattamid, Mohammed, Schaback, Robert
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Future Internet, 2016 The Windows Operating System (OS) is the most popular desktop OS in the world, as it has the majority market share of both servers and personal computing necessities. However, as its default signature-based security measures are ineffectual for detecting
Waqas Haider +3 more
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, 2016 Kernel mean embeddings have recently attracted the attention of the machine learning community. They map measures $ $ from some set $M$ to functions in a reproducing kernel Hilbert space (RKHS) with kernel $k$. The RKHS distance of two mapped measures is a semi-metric $d_k$ over $M$. We study three questions.
Simon-Gabriel, C., Schölkopf, B.
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Multiple Kernel k-means with Incomplete Kernels [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Multiple kernel clustering (MKC) algorithms optimally combine a group of pre-specified base kernel matrices to improve clustering performance. However, existing MKC algorithms cannot efficiently address the situation where some rows and columns of base kernel matrices are absent.
Liu, Xinwang +9 more
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Bounded and multiperiodic solutions of the system of partial integro-differential equations
Қарағанды университетінің хабаршысы. Математика сериясы, 2019 The system of partial integro - differential equations with an operator of differentiation with respect to directions of vector field is considered. The considering integro - differential equation does not contain space variables.
G.M. Aitenova +3 more
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End-to-End Neural Ad-hoc Ranking with Kernel Pooling [PDF]
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017 This paper proposes K-NRM, a kernel based neural model for document ranking. Given a query and a set of documents, K-NRM uses a translation matrix that models word-level similarities via word embeddings, a new kernel-pooling technique that uses kernels ...
Chenyan Xiong +4 more
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Generalized Shortest Path Kernel on Graphs
, 2015 We consider the problem of classifying graphs using graph kernels. We define a new graph kernel, called the generalized shortest path kernel, based on the number and length of shortest paths between nodes.
A Fronczak +6 more
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