Results 231 to 240 of about 394,763 (294)

Investigation of in silico studies for cytochrome P450 isoforms specificity. [PDF]

Comput Struct Biotechnol J
Wei Y, Palazzolo L, Ben Mariem O, Bianchi D, Laurenzi T, Guerrini U, Eberini I.   +6 more
europepmc   +1 more source

Artificial neural networks fighting real neural decline: a systematic review of AI in Alzheimer's research. [PDF]

Artif Intell Rev
Mou FS, Ahmed T, Huda MN, Nandi AK.
europepmc   +1 more source

Shared-Memory Parallel Edmonds Blossom Algorithm for Maximum Cardinality Matching in General Graphs. [PDF]

IEEE Int Symp Parallel Distrib Process Workshops Phd Forum
Schwing G, Grosu D, Schwiebert L.
europepmc   +1 more source

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Kernelization for Counting Problems on Graphs: Preserving the Number of Minimum Solutions

International Symposium on Parameterized and Exact Computation, 2023
A kernelization for a parameterized decision problem Q is a polynomial-time preprocessing algorithm that reduces any parameterized instance (x, k) into an instance (x', k') whose size is bounded by a function of k alone and which has the same yes/no ...
B. Jansen, Bart van der Steenhoven
semanticscholar   +1 more source

Surface Defects Detection Using Non-convex Total Variation Regularized RPCA With Kernelization

IEEE Transactions on Instrumentation and Measurement, 2021
Surface defects have an adverse effect on the quality of industrial products, and vision-based defect detection is widely researched due to its objective and stable performance.
Junpu Wang, Guili Xu, Chunlei Li, Zhengsheng Wang, Fuju Yan   +4 more
semanticscholar   +1 more source

Kernel Factory: An ensemble of kernel machines [PDF]

Expert Systems with Applications, 2013
We propose an ensemble method for kernel machines. The training data is randomly split into a number of mutually exclusive partitions defined by a row and column parameter. Each partition forms an input space and is transformed by an automatically selected kernel function into a kernel matrix K.
Michel Ballings, Dirk Van den Poel
openaire   +1 more source

Kernelization Lower Bounds Through Colors and IDs

ACM Transactions on Algorithms, 2014
Saket Saurabh, Daniel Lokshtanov, Michael Dom   +2 more
exaly   +2 more sources

Review of Kernelization

Sigact News, 2020
On the surface, the concept of preprocessing may not seem particularly novel nor insightful. Indeed, the simple idea that putting in computational effort upfront may pay off in dividends of time saved later is not only advice that we have received ...
F. Fomin, D. Lokshtanov, Saket Saurabh, M. Zehavi   +3 more
semanticscholar   +1 more source

A general kernelization technique for domination and independence problems in sparse classes

International Symposium on Parameterized and Exact Computation, 2020
We unify and extend previous kernelization techniques in sparse classes [5, 16] by defining a structure we call water lilies and show how it can be used in bounded expansion classes to construct linear bikernels for $(r, c)$-DOMINATING SET, $(r, c ...
Carl Einarson, F. Reidl
semanticscholar   +1 more source