kernel-methods

A Matlab benchmarking toolbox for kernel adaptive filtering

Kernel Methods Toolbox for Matlab/Octave

This is the page for the book Digital Signal Processing with Kernel Methods.

implementation of a Deep Kernelized Auto Encoder for learning vectorial representations of mutlivariate time series with missing data.

UAI 2015. Kernel-based just-in-time learning for expectation propagation

Implementations of gradKCCA

Anomaly detection on a production line using principal component analysis (PCA) and kernel principal component analysis (KPCA) *from scratch*.

AISTATS 2016. K2-ABC: Approximate Bayesian Computation with Kernel Embeddings.

Enitor provides the MATLAB implementation of several large-scale kernel methods.

Using ε-Support Vector Regression (ε-SVR) for identification of Linear Parameter Varying (LPV) dynamical systems

This work shows that least-square estimation (mean calculation) in a reproducing kernel Hilbert space (RKHS) F corresponds to different M-estimators in the original space depending on the kernel function associated with F. In particular, we present a proof of the correspondence of mean estimation in an RKHS for the Gaussian kernel

Kernel Distance Metric Learning using Pairwise Constraints for Person Re-Identification

Finite-Sample Integral Gaussian Processes

MATLAB implementation of SCCA-HSIC

An Octave/Matlab mini benchmarking toolbox for Kernel Adaptive Filtering and Neural Networks

Implementation of the paper "Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels"

Code for our paper: "Adaptive Geo-Topological Independence Criterion".

MATLAB implementation of FedHK-MVFC

Machine Learning and Analysis of Big Data course, Computer Science M.Sc., Ben Gurion University of the Negev, 2020

Kernel Perceptron (Matlab)