Semi‐supervised multiple empirical kernel learning with pseudo empirical loss and similarity regularization
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22690
Abstract: Multiple empirical kernel learning (MEKL) is a scalable and efficient supervised algorithm based on labeled samples. However, there is still a huge amount of unlabeled samples in the real‐world application, which are not applicable for… read more here.
Keywords: labeled samples; empirical kernel; unlabeled samples; kernel learning ... See more keywords
Fenchel duality of Cox partial likelihood with an application in survival kernel learning
Sign Up to like & getrecommendations! Published in 2021 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2021.102077
Abstract: The Cox proportional hazard model is one of the most widely used methods in modeling time-to-event data in the health sciences. Due to the simplicity of the Cox partial likelihood function, many machine learning algorithms… read more here.
Keywords: cox partial; kernel learning; fenchel duality; partial likelihood ... See more keywords
A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD
Sign Up to like & getrecommendations! Published in 2017 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2016.12.007
Abstract: OBJECTIVE The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). METHODS In this paper, we describes a new CT lung CAD method which… read more here.
Keywords: feature; cad; method; multi kernel ... See more keywords
Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.09.117
Abstract: Abstract The advent of the Social Web has enabled anyone with an Internet connection to easily create and share their ideas, opinions and content with millions of other people around the world. In pace with… read more here.
Keywords: multiple kernel; analysis; multimodal sentiment; kernel learning ... See more keywords
DWS-MKL: Depth-width-scaling multiple kernel learning for data classification
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.06.039
Abstract: Abstract Deep learning technologies have been rapidly developing recently. They have shown excellent performances in many fields. However, deep learning networks have weak adaptability to small sample sizes. Usually, deep learning networks require tens of… read more here.
Keywords: classification; multiple kernel; deep learning; kernel learning ... See more keywords
Resting state dynamics meets anatomical structure: Temporal multiple kernel learning (tMKL) model
Sign Up to like & getrecommendations! Published in 2019 at "NeuroImage"
DOI: 10.1016/j.neuroimage.2018.09.054
Abstract: &NA; Over the last decade there has been growing interest in understanding the brain activity, in the absence of any task or stimulus, captured by the resting‐state functional magnetic resonance imaging (rsfMRI). The resting state… read more here.
Keywords: state; multiple kernel; kernel learning; model ... See more keywords
A smart diagnostic tool based on deep kernel learning for on-site determination of phosphate, calcium, and magnesium concentration in a hydroponic system
Sign Up to like & getrecommendations! Published in 2021 at "RSC Advances"
DOI: 10.1039/d1ra00140j
Abstract: A smart diagnostic tool based on deep kernel learning for on-site determining phosphate, calcium, and magnesium concentration in a hydroponic system. read more here.
Keywords: diagnostic tool; smart diagnostic; deep kernel; tool based ... See more keywords
Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac488
Abstract: Differentiating cancer subtypes is crucial to guide personalized treatment and improve the prognosis for patients. Integrating multi-omics data can offer a comprehensive landscape of cancer biological process and provide promising ways for cancer diagnosis and… read more here.
Keywords: multi omics; kernel learning; multi kernel; multi ... See more keywords
Ensembled Transfer Learning and Multiple Kernel Learning for Phonocardiogram Based Atherosclerotic Coronary Artery Disease Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3140277
Abstract: Conventional machine learning has paved the way for a simple, affordable, non-invasive approach for Coronary artery disease (CAD) detection using phonocardiogram (PCG). It leaves a scope to explore improvement of performance metrics by fusion of… read more here.
Keywords: kernel learning; multiple kernel; artery disease; detection ... See more keywords
Ideal Kernel-Based Multiple Kernel Learning for Spectral-Spatial Classification of Hyperspectral Image
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2695534
Abstract: Using multiple types of features can effectively improve the classification accuracy of hyperspectral image (HSI). Multiple kernel learning (MKL) provides a flexible framework to fuse different features in a very natural way. In this letter,… read more here.
Keywords: ideal kernel; classification; multiple kernel; kernel learning ... See more keywords
Multi-View Kernel Learning for Identification of Disease Genes.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2023.3247033
Abstract: Gene expression data sets and protein-protein interaction (PPI) networks are two heterogeneous data sources that have been extensively studied, due to their ability to capture the co-expression patterns among genes and their topological connections. Although… read more here.
Keywords: disease genes; kernel learning; multi view; view kernel ... See more keywords