Results 1 to 10 of about 394,763 (294)
Searching and Indexing Genomic Databases via Kernelization [PDF]
Frontiers in Bioengineering and Biotechnology, 2015 The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes.
Simon Puglisi +2 more
exaly +4 more sources
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2016 In this paper we propose a new framework for analyzing the performance of preprocessing algorithms. Our framework builds on the notion of kernelization from parameterized complexity.
D. Lokshtanov +3 more
semanticscholar +5 more sources
Adaptive kernel fuzzy clustering for missing data [PDF]
PLoS ONE, 2021 Many machine learning procedures, including clustering analysis are often affected by missing values. This work aims to propose and evaluate a Kernel Fuzzy C-means clustering algorithm considering the kernelization of the metric with local adaptive ...
Anny K. G. Rodrigues +2 more
doaj +3 more sources
A Tensorized Multitask Deep Learning Network for Progression Prediction of Alzheimer’s Disease [PDF]
Frontiers in Aging Neuroscience, 2022 With the advances in machine learning for the diagnosis of Alzheimer’s disease (AD), most studies have focused on either identifying the subject’s status through classification algorithms or on predicting their cognitive scores through regression methods,
Solale Tabarestani +18 more
doaj +2 more sources
Survival parametric modeling for patients with heart failure based on Kernel learning [PDF]
BMC Medical Research MethodologyTime-to-event data are very common in medical applications. Regression models have been developed on such data especially in the field of survival analysis.
Maryam Montaseri +4 more
doaj +2 more sources
Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging [PDF]
Frontiers in Neuroinformatics, 2016 In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables.
Natalia Y Bilenko +2 more
doaj +2 more sources
A 2k-kernelization algorithm for vertex cover based on crown decomposition
Theoretical Computer Science, 2018 We revisit crown decomposition for the Vertex Cover problem by giving a simple 2 k -kernelization algorithm. Previously, a 2 k kernel was known but it was computed using both crown decomposition and linear programming; moreover, with crown decomposition ...
Wenjun Li, Binhai Zhu
exaly +2 more sources
Kernelization of Cycle Packing with Relaxed Disjointness Constraints
SIAM Journal on Discrete Mathematics, 2018 A key result in the field of kernelization, a subfield of parameterized complexity, states that the classic Disjoint Cycle Packing problem, i.e. finding k vertex disjoint cycles in a given graph G, admits no polynomial kernel unless NP subseteq coNP/poly.
Saket Saurabh +2 more
exaly +2 more sources
Kernelization for Spreading Points [PDF]
Embedded Systems and Applications, 2023 We consider the following problem about dispersing points. Given a set of points in the plane, the task is to identify whether by moving a small number of points by small distance, we can obtain an arrangement of points such that no pair of points is ...
F. Fomin +4 more
semanticscholar +1 more source
Kernelization of Counting Problems [PDF]
Information Technology Convergence and Services, 2023 We introduce a new framework for the analysis of preprocessing routines for parameterized counting problems. Existing frameworks that encapsulate parameterized counting problems permit the usage of exponential (rather than polynomial) time either ...
D. Lokshtanov +3 more
semanticscholar +1 more source