Reproducibility is imperative for any scientific discovery. More often than not, modern scientific findings rely on statistical analysis of high-dimensional data. At a minimum, reproducibility manifests itself in stabili

Source URL: mmds-data.org

• Statistics
• Machine learning
• Computational statistics
• Statistical models
• Statistical theory
• Statistical inference
• Bootstrapping
• Cross-validation
• Stability

Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series Hoang-Vu Nguyen◦ Jilles Vreeken◦

Source URL: eda.mmci.uni-saarland.de

• Statistics
• Multivariate statistics
• Machine learning
• Dimension reduction
• Principal component analysis
• Numerical analysis
• Dimensionality reduction
• Curse of dimensionality
• KullbackLeibler divergence
• Divergence
• Pattern recognition
• Normal distribution

An Interactive Visual Testbed System for Dimension Reduction and Clustering of Large-scale High-dimensional Data Jaegul Choo, Hanseung Lee, Zhicheng Liu, John Stasko, and Haesun Park Georgia Institute of Technology, USA

Source URL: www.zcliu.org

• Visualization
• Multivariate statistics
• Dimension reduction
• Data
• Data visualization
• Information technology governance
• K-means clustering
• Parallel coordinates
• Principal component analysis
• Information visualization
• Spectral clustering
• Data analysis

Several problems in applied mathematics and statistics require integrating a function f over a high-dimensional domain. For example, estimating the partition function of a graphical model for a fixed set of parameters re

Source URL: mmds-data.org

Unsupervised Dimensionality Estimation and Manifold Learning in high-dimensional Spaces by Tensor Voting Philippos Mordohai and G´erard Medioni University of Southern California email: {mordohai,medioni}@iris.usc.edu

Source URL: www.cs.stevens.edu

• Multivariate statistics
• Dimension reduction
• Riemannian geometry
• Machine learning
• Computational statistics
• Tensor
• Nonlinear dimensionality reduction
• Dimensionality reduction
• Isomap
• LaplaceBeltrami operator
• Manifold
• Metric tensor

Reproducibility is imperative for any scientific discovery. More often than not, modern scientific findings rely on statistical analysis of high-dimensional data. At a minimum, reproducibility manifests itself in stabili

Source URL: mmds-data.org

• Machine learning
• Computational statistics
• Statistical models
• Statistical theory
• Statistical inference
• Bootstrapping
• Cross-validation
• Statistics
• Stability

Visual Interactive Neighborhood Mining on High Dimensional Data Emin Aksehirli • Bart Goethals •

Source URL: poloclub.gatech.edu

• Multivariate statistics
• Cluster analysis
• Data mining
• Geostatistics
• K-means clustering
• Hierarchical clustering
• Dimension reduction
• K-nearest neighbors algorithm
• Machine learning
• Multidimensional scaling
• Pattern recognition
• Nonlinear dimensionality reduction

High-dimensional neural spike train analysis with generalized count linear dynamical systems Lars Buesing Department of Statistics Columbia University

Source URL: stat.columbia.edu

Empirical Likelihood Test for High Dimensional Linear Models Liang Peng1 , Yongcheng Qi2 and Ruodu Wang3 January 7, 2014 Abstract We propose an empirical likelihood method to test whether the coefficients in a possibly h

Source URL: sas.uwaterloo.ca

• Statistics
• Statistical theory
• Estimation theory
• Regression analysis
• Probability distributions
• Parametric statistics
• Bayesian statistics
• Normal distribution
• Linear regression
• Likelihood function

Effect of heavy tails on ultra high dimensional variable ranking methods Aurore Delaigle and Peter Hall Department of Mathematics and Statistics, University of Melbourne, Australia. Abstract: Contemporary problems invol

Source URL: www.ms.unimelb.edu.au