Results 41 to 50 of about 845,859 (278)
Kernel Block Diagonal Representation Subspace Clustering with Similarity Preservation
Applied Sciences, 2023 Subspace clustering methods based on the low-rank and sparse model are effective strategies for high-dimensional data clustering. However, most existing low-rank and sparse methods with self-expression can only deal with linear structure data effectively,
Yifang Yang, Fei Li
doaj +1 more source
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) [PDF]
, 2015 We introduce a new structured kernel interpolation (SKI) framework, which generalises and unifies inducing point methods for scalable Gaussian processes (GPs).
Nickisch, Hannes, Wilson, Andrew Gordon
core +2 more sources
The McCance Brain Care Score and Mortality: Evidence From a Large‐Scale Population‐Based Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives This study aimed to examine the relationship between the McCance Brain Care Score (BCS) and mortality in the general population. Methods We conducted a prospective, population‐based cohort study using data from the UK Biobank. Participants with complete data enabling calculation of BCS and full mortality information were included ...
Zhiqiang Xu, Xiaoxiao Wang, Nan Li
wiley +1 more source
Iraqi Journal for Computer Science and Mathematics, 2023 Statistical modeling is essential in many scientific research areas because it explains the relationship between the response variable of interest and a number of explanatory variables.
Zakariya Algamal +2 more
doaj +1 more source
Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim +3 more
wiley +1 more source
Information-Geometric Models in Data Analysis and Physics
MathematicsInformation geometry provides a data-informed geometric lens for understanding data or physical systems, treating data or physical states as points on statistical manifolds endowed with information metrics, such as the Fisher information.
D. Bernal-Casas, José M. Oller
doaj +1 more source
On the Complexity of Learning with Kernels [PDF]
, 2014 A well-recognized limitation of kernel learning is the requirement to handle a kernel matrix, whose size is quadratic in the number of training examples.
Cesa-Bianchi, Nicolò +2 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
Improving Speaker Recognition in Environmental Noise With Adaptive Filter
IEEE Access, 2022 Speaker recognition is challenging in real-world environments. Typically, studies approach noises only in an additive manner. However, real environments commonly present reverberating conditions that worsen speech processing.
Vinicius Almeida Dos Santos +4 more
doaj +1 more source
Kernel Mean Shrinkage Estimators [PDF]
, 2016 A mean function in a reproducing kernel Hilbert space (RKHS), or a kernel mean, is central to kernel methods in that it is used by many classical algorithms such as kernel principal component analysis, and it also forms the core inference step of modern ...
Fukumizu, Kenji +4 more
core +2 more sources