Results 11 to 20 of about 708,932 (315)
Entropy, 2021 The pervasive presence of artificial intelligence (AI) in our everyday life has nourished the pursuit of explainable AI. Since the dawn of AI, logic has been widely used to express, in a human-friendly fashion, the internal process that led an (intelligent) system to deliver a specific output.
Mirko Polato, Fabio Aiolli
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Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017 58 pages. Version 2 contain new results: PSAKS for Cycle Packing and approximate kernel lower bounds for Set Cover and Hitting Set parameterized by universe ...
Lokshtanov, D. +3 more
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Advances in Data Science and Adaptive Analysis, 2019 A new method for hierarchical clustering of data points is presented. It combines treelets, a particular multiresolution decomposition of data, with a mapping on a reproducing kernel Hilbert space. The proposed approach, called kernel treelets (KT), uses this mapping to go from a hierarchical clustering over attributes (the natural output of treelets)
Hedi Xia, Héctor D. Ceniceros
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Journal of the ACM, 2009 In a parameterized problem, every instance I comes with a positive integer k . The problem is said to admit a polynomial kernel if, in polynomial time, one can reduce the size of the instance I to a polynomial in k while preserving the answer ...
Hans L. Bodlaender +5 more
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Horticulturae, 2023 This study was carried out to determine the fatty acid composition, bioactive compounds, and mineral element content of standard hazelnut cultivars and accessions from the Eastern Black Sea region.
Mehmet Yaman +6 more
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Bidimensionality and Kernels [PDF]
SIAM Journal on Computing, 2010 Bidimensionality Theory was introduced by [E.D. Demaine, F.V. Fomin, M.Hajiaghayi, and D.M. Thilikos. Subexponential parameterized algorithms on graphs of bounded genus and H-minor-free graphs, J. ACM, 52 (2005), pp.866--893] as a tool to obtain sub-exponential time parameterized algorithms on H-minor-free graphs. In [E.D.
Fedor V. Fomin +3 more
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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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, 2016 We introduce the Mondrian kernel, a fast random feature approximation to the Laplace kernel. It is suitable for both batch and online learning, and admits a fast kernel-width-selection procedure as the random features can be re-used efficiently for all kernel widths.
Balog, M +4 more
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A survey of kernel and spectral methods for clustering [PDF]
, 2007 Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with a special interest in two recent approaches: kernel and spectral methods ...
Masulli, F. +11 more
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Computation, 2022 This study aims at developing models in analyzing the results of proficiency testing (PT) schemes for a limited number of participants. The models can determine the best estimators of location and dispersion using unsatisfactory results as a criterion by
Dimitris Tsamatsoulis
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