GPU-based Exact Closest/Furthest Pair Search

Code for the paper E. Raninen, D. E. Tyler and E. Ollila, "Linear pooling of sample covariance matrices," in IEEE Transactions on Signal Processing, Vol 70, pp. 659-672, 2022, doi: 10.1109/TSP.2021.3139207.

A pure implementation for sparse denoising autoencoder with adaptive evolutionary training using Scipy. The sparse implementation makes the algorithm scalable to high dimensional data and trainable on CPUs.

Hypersphere volume computation for low dimensionality using Monte Carlo techniques and threaded Ruby

K-means Forest Algorithm

Modern Logistic Regression for High Dimensional Data

MCMC for spike and slab survival models

A python toolbox for visualizing and manipulating high-dimensional data

A simple library for t-SNE animation and a zoom-in feature to apply t-SNE in that region

Bayesian regression with shrinkage priors

Nonconvex Penalized Estimation for Generalized Linear Models

We explored various approaches to deal with high-dimensional data in this study, and we compared them using simulation and soil datasets. We discovered that grouping had a significant impact on model correctness and error reduction. For the core projection step, we first looked at the properties of all the algorithms and how they function to com…

Unofficial fork of Norio Katayama's SR Tree spatial indexing implementation for high-dimensional data

An advanced version of K-Means using Particle swarm optimization for clustering of high dimensional data sets, which converges faster to the optimal solution.

High-Dimensional Similarity Learning

A general purpose Snakemake workflow to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.

R package providing statistical tests for high-dimensional repeated measures or split-plot designs.