Results 11 to 20 of about 111,097 (310)

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.
Travis Gagie, Simon J Puglisi
exaly   +4 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, Raydonal Ospina, Marcelo R. P. Ferreira   +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, Mohammad Eslami, Mercedes Cabrerizo, Rosie E. Curiel, Rosie E. Curiel, Armando Barreto, Naphtali Rishe, David Vaillancourt, David Vaillancourt, David Vaillancourt, Steven T. DeKosky, Steven T. DeKosky, David A. Loewenstein, David A. Loewenstein, David A. Loewenstein, Ranjan Duara, Ranjan Duara, Malek Adjouadi, Malek Adjouadi   +18 more
doaj   +2 more sources

Regularization and Kernelization of the Maximin Correlation Approach

IEEE Access, 2016
Robust classification becomes challenging when each class consists of multiple subclasses. Examples include multi-font optical character recognition and automated protein function prediction.
Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon   +3 more
doaj   +3 more sources

Lossy Kernelization [PDF]

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.
Lokshtanov, Daniel, Panolan, Fahad, Ramanujan, M. S., Saurabh, Saket   +3 more
core   +3 more sources

Survival parametric modeling for patients with heart failure based on Kernel learning [PDF]

BMC Medical Research Methodology
Time-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, Mansour Rezaei, Armin Khayati, Shayan Mostafaei, Mohammad Taheri   +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, Jack L Gallant, Jack L Gallant   +2 more
doaj   +2 more sources

Propositional Kernels [PDF]

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
openaire   +3 more sources

Expansion Lemma—Variations and Applications to Polynomial-Time Preprocessing

Algorithms, 2023
In parameterized complexity, it is well-known that a parameterized problem is fixed-parameter tractable if and only if it has a kernel—an instance equivalent to the input instance, whose size is just a function of the parameter.
Ashwin Jacob, Diptapriyo Majumdar, Venkatesh Raman   +2 more
doaj   +1 more source

Clique Search in Graphs of Special Class and Job Shop Scheduling

Mathematics, 2022
In this paper, we single out the following particular case of the clique search problem. The vertices of the given graph are legally colored with k colors and we are looking for a clique with k nodes in the graph.
Sándor Szabó, Bogdán Zaválnij
doaj   +1 more source