Skip to main navigation
Skip to search
Skip to main content
Aston Research Explorer Home
Help & FAQ
Home
Research units
Profiles
Research output
Datasets
Student theses
Activities
Press/Media
Prizes
Equipment
Search by expertise, name or affiliation
Generalized KPCA by adaptive rules in feature space
Yanwei Pang, Lei Wang, Yuan Yuan
*
*
Corresponding author for this work
Computer Science Research Group
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Generalized KPCA by adaptive rules in feature space'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Adaptation Rules
100%
Binary Field
25%
Dimensionality Reduction
25%
Feature Space
100%
Generalized Kernel
100%
Gibbs Distribution
25%
Gradient Method
25%
Hebbian
25%
High-dimensional Feature Space
25%
Iterative Manner
25%
Kernel Principal Component Analysis
100%
Kernel Trick
25%
Marginal Distribution
25%
Nonlinear Structures
25%
Novel Algorithm
25%
Optimization Problem
50%
Principal Coordinate Analysis (PCoA)
25%
Robust Kernel
25%
Robust Principal Component Analysis
50%
Statistical Analysis
25%
Stochastic Gradient Descent
25%
Synthetic Data
25%
Engineering
Component Analysis
100%
Dimensional Feature Space
33%
Dimensionality
33%
Experimental Result
33%
Feature Space
100%
Gibbs Distribution
33%
Gradient Descent
33%
Input Data
33%
Marginal Distribution
33%
Optimisation Problem
66%
Principal Components
100%
Statistical Data
33%
Computer Science
Component Analysis
100%
Dimensional Feature Space
33%
Dimensionality Reduction
33%
Experimental Result
33%
Feature Space
100%
Gibbs Distribution
33%
Gradient Descent
33%
Marginal Distribution
33%
Optimization Problem
66%
Principal Components
100%
Statistical Data
33%
Synthetic Data
33%
Mathematics
Binary Field
14%
Dimensional Feature Space
14%
Dimensionality Reduction
14%
Feature Space
100%
Gibbs Distribution
14%
Input Data
14%
Marginal Distribution
14%
Principal Component Analysis
100%
Stochastics
14%
Synthetic Data
14%