Results 11 to 20 of about 234,193 (264)
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 ...
Daniel Lokshtanov +3 more
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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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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, Hector D. Ceniceros
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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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Вавиловский журнал генетики и селекции, 2018 Sunflower broomrape is a parasitic chlorophyll plant that affects the root system of the host plant, absorbing water, nutrients and toxic products from it. Germination of broomrape seeds occurs due to strigolactones released into the soil by the roots of
S. G. Hablak +2 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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, 2023 This chapter introduces a powerful class of machine learning approaches called kernel methods, which present an alternative to arguably more widely known neural network approaches. Kernel methods can learn even highly nonlinear problems by making an implicit transformation from a low-dimensional input space into a higher-dimensional feature space. This
Pinheiro Jr, Max, Dral, Pavlo
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PERFORMANCE ENHANCEMENT OF CUDA APPLICATIONS BY OVERLAPPING DATA TRANSFER AND KERNEL EXECUTION [PDF]
Applied Computer Science, 2021 The CPU-GPU combination is a widely used heterogeneous computing system in which the CPU and GPU have different address spaces. Since the GPU cannot directly access the CPU memory, prior to invoking the GPU function the input data must be available on ...
K. RAJU, Niranjan N CHIPLUNKAR
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Subsampling Realised Kernels [PDF]
SSRN Electronic Journal, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Barndorff-Nielsen, Ole Eiler +3 more
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