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Nature, ISSN 0028-0836, 03/2019, Volume 567, Issue 7747, pp. 209 - 212
...) being the best known method for classification problems. However, there are limitations to the successful solution to such classification problems when the feature space... 
FERMI | RESISTIVITY | MULTIDISCIPLINARY SCIENCES | CRITICAL-POINT | Usage | Quantum computing | Methods | Machine learning | Classifiers | Kernel functions | Circuits | Data processing | Entanglement | Pattern recognition | Quantum computers | Exploitation | Support vector machines | Kernels | Learning | Learning algorithms | Problems | Algorithms | Microprocessors | Classification | Computer applications | Artificial intelligence | Quantum theory
Journal Article
Physical Review Letters, ISSN 0031-9007, 02/2019, Volume 122, Issue 4, p. 040504
.... We interpret the process of encoding inputs in a quantum state as a nonlinear feature map that maps data to quantum Hilbert space... 
PHYSICS, MULTIDISCIPLINARY | Kernels | Support vector machines | Feature maps | Quantum computing | Algorithms | Maps | Machine learning | Hilbert space | Artificial intelligence | Quantum theory | Quantum computers | Continuity (mathematics)
Journal Article
Neurocomputing, ISSN 0925-2312, 03/2014, Volume 128, pp. 88 - 95
...), is a unified learning platform that can use a widespread type of feature mappings. In theory, ELM can approximate any target continuous function and classify any disjoint regions... 
Extreme learning machine (ELM) | ELM feature space | ELM kMeans | Nonnegative matrix factorization (NMF) | ELM NMF clustering | Data clustering | KERNEL | EFFICIENT ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms | Learning | Approximation | Mathematical analysis | Elm | Mapping | Clustering | Factorization | Neural networks
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 05/2002, Volume 24, Issue 5, pp. 603 - 619
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 08/2008, Volume 9, pp. 1875 - 1908
... economical use of feature space dimensions. In the best case, kernels provide efficient implicit representations of the data for supervised learning problems... 
Effective dimensionality | Dimension reduction | Kernel methods | Feature space | SUPPORT VECTOR MACHINES | MATRIX | feature space | BOUNDS | effective dimensionality | kernel methods | ERROR | COMPONENT ANALYSIS | dimension reduction | OPERATORS | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Pattern Recognition, ISSN 0031-3203, 2009, Volume 42, Issue 11, pp. 2671 - 2683
.... The proposed framework enables informative integration of possibly heterogeneous sources in a multitude of ways, from the simple summation of feature expansions to weighted product of kernels... 
Information integration | Kernel combination | Hierarchical Bayes | Variational Bayes approximation | Bayesian inference | Ensemble learning | Multiclass classification | Multi-modal modelling | EMPIRICAL-ANALYSIS | PROTEIN FOLD RECOGNITION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | KERNEL | Markov processes | Monte Carlo method | Universities and colleges | Analysis
Journal Article
IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, 01/2014, Volume 11, Issue 1, pp. 288 - 292
... (often called multispectral). A new strategy is proposed, where the spectral dimensionality of the multispectral data is first expanded by using nonlinear feature extraction with kernel methods such as kernel principal component analysis... 
Radio frequency | random forests (RFs) | Feature extraction | kernel principal component analysis (KPCA) | spectral-spatial classification | Kernel | Spatial resolution | Hyperspectral imaging | Extended multiattribute profiles (EMAPs) | support vector machines (SVMs) | GEOCHEMISTRY & GEOPHYSICS | REMOTE SENSING | MORPHOLOGICAL PROFILES | ATTRIBUTE PROFILES | HYPERSPECTRAL DATA | ENGINEERING, ELECTRICAL & ELECTRONIC | Principal components analysis | Spectrum analysis | Remote sensing
Journal Article
IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, 09/2011, Volume 8, Issue 5, pp. 894 - 898
...) analysis as a popular method for feature extraction and dimensionality reduction. Linear methods such as LDA work well for unimodal Gaussian class-conditional distributions... 
Training | Dimensionality reduction | hyperspectral imagery (HSI) | Accuracy | feature space | kernel methods | Kernel | Pixel | Hyperspectral imaging | GEOCHEMISTRY & GEOPHYSICS | REMOTE SENSING | FUSION | TARGET RECOGNITION | SELECTION | ENGINEERING, ELECTRICAL & ELECTRONIC | Studies | Discriminant analysis | Methods | Kernels | Tasks | Classification | Images | Gaussian | Subspaces | Image classification
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 05/2012, Volume 13, pp. 1393 - 1434
We introduce a framework for feature selection based on dependence maximization between the selected features and the labels of an estimation problem, using the Hilbert-Schmidt Independence Criterion... 
Kernel methods | Feature selection | Hilbert space embedding of distribution | Hilbert-Schmidt Independence Criterion | Independence measure | MICROARRAY | GENE-EXPRESSION PROFILES | CLASSIFICATION | SHRUNKEN CENTROIDS | Hilbert-Schmidt independence criterion | CANCER | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | independence measure | kernel methods | feature selection | PREDICT SURVIVAL | AUTOMATION & CONTROL SYSTEMS
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 06/2018, Volume 27, Issue 6, pp. 2980 - 2995
.... Taking advantage of kernel function in efficiently describing intrinsic features, we further conduct the patch-based reconstruction model in the high-dimensional kernel space for capturing nonlinear characteristics... 
Training | Geometry | Image resolution | Image edge detection | super-resolution | Face hallucination | kernel method | regularization framework | Face | Kernel | Image reconstruction | manifold learning | SUPERRESOLUTION | REGRESSION | SPARSITY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Analysis and Applications, ISSN 0219-5305, 01/2018, Volume 16, Issue 1, pp. 1 - 54
This paper proposes a unified framework for the investigation of constrained learning theory in reflexive Banach spaces of features via regularized empirical risk minimization... 
feature map | statistical learning | empirical risk | totally convex function | representer theorem | Consistency | regularization | Banach spaces | reproducing kernel | REGRESSION | SPARSITY | MATHEMATICS, APPLIED | INEQUALITIES | KERNEL HILBERT-SPACES | MATHEMATICS | RATES | MINIMIZATION | CONVERGENCE | SELECTION | UNIFORMLY CONVEX
Journal Article
Algorithms, ISSN 1999-4893, 05/2018, Volume 11, Issue 5, p. 62
.... Therefore, the construction of the kernel space may not be reasonable. In the paper, a Feature-Weighted SVR (FW-SVR) is presented... 
Feature-weighted | Support vector regression | Data pre-processing | Contribution | Support vector machines | Kernel functions | Data sets | support vector regression | contribution | feature-weighted | data pre-processing
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 04/2018, Volume 66, Issue 7, pp. 1920 - 1932
.... So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS... 
Training | Support vector machines | RKHS | KLMS | Signal processing algorithms | Estimation | distributed | Hilbert space | Diffusion | Kernel | online learning | LMS | RECURSIVE LEAST-SQUARES | CLASSIFICATION | NYSTROM METHOD | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer Science - Learning
Journal Article
Pattern Recognition, ISSN 0031-3203, 2009, Volume 42, Issue 5, pp. 710 - 717
.... This makes the training process time-consuming. In this paper we propose using the inter-cluster distances in the feature spaces to choose the kernel parameters... 
Support vector machines | Inter-cluster distances | SVM | Kernel parameters | DECOMPOSITION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article