Localized Multiple Kernel Learning for Anomaly Detection: One-class Classification

Published in

Knowledge-Based Systems(2018)

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TL;DR

A Localized Multiple Kernel learning approach for Anomaly Detection (LMKAD) using OCC, where the weight for each kernel is assigned locally and the parameters of the gating function and one-class classifier are optimized simultaneously through a two-step optimization process.

Authors

C. Gautam

1 papers

R. Balaji

1 papers

S. K

1 papers

Aruna Tiwari

1 papers

K. Ahuja

1 papers

References46 items

Nested SVDD in DAG SVM for induction motor condition monitoring

Multiple kernel approach to semi-supervised fuzzy clustering algorithm for land-cover classification

Localized Multiple Kernel Learning With Dynamical Clustering and Matrix Regularization

Multiple kernel learning using composite kernel functions

An innovative one-class least squares support vector machine model based on continuous cognition

Localized Multiple Kernel Learning for Anomaly Detection: One-class Classification

Published in

Knowledge-Based Systems(2018)

External Links:

Generate Graph DownloadPDF

TL;DR

Authors

C. Gautam

1 papers

R. Balaji

1 papers

S. K

1 papers

Aruna Tiwari

1 papers

K. Ahuja

1 papers

References46 items

Nested SVDD in DAG SVM for induction motor condition monitoring

Multiple kernel approach to semi-supervised fuzzy clustering algorithm for land-cover classification

Localized Multiple Kernel Learning With Dynamical Clustering and Matrix Regularization

Multiple kernel learning using composite kernel functions

An innovative one-class least squares support vector machine model based on continuous cognition

An one-class classification support vector machine model by interval-valued training data

Dynamic classifier selection for one-class classification

Multiple empirical kernel learning with locality preserving constraint

A boundary-fixed negative selection algorithm with online adaptive learning under small samples for anomaly detection

One-Class Support Tensor Machine

Hidden Markov Anomaly Detection

Localized Multiple Kernel Learning - A Convex Approach

One-Class Classification with Extreme Learning Machine

Using one-class classifiers and multiple kernel learning for defining imprecise geographic regions

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A review of novelty detection

Cytological image analysis with firefly nuclei detection and hybrid one-class classification decomposition

A new one-class SVM based on hidden information

Two-stage multiple kernel learning with multiclass kernel polarization

$L_{p}$ Norm Localized Multiple Kernel Learning via Semi-Definite Programming

Sparse Solutions for Single Class SVMs: A Bi-Criterion Approach

LIBSVM: A library for support vector machines

Multiple Kernel Learning Algorithms

Localized Multiple Kernel Regression

Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study

Fabric defect detection based on multiple fractal features and support vector data description