STAT 416: H IGH D IMENSIONAL S TATISTICS II Syllabus, Spring 2016 High dimensional statistics II is graduate level course on the mathematical and statistical properties of estimation and inference procedures on high dime

Source URL: galton.uchicago.edu

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

That was fast! Speeding up NN search of high dimensional distributions. Emanuele Coviello University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093

Source URL: eceweb.ucsd.edu

• Statistics
• Geometry
• Statistical distance
• Information
• Statistical theory
• Information theory
• Bregman divergence
• Search algorithms
• KullbackLeibler divergence
• Variational Bayesian methods
• Expectationmaximization algorithm
• Divergence

INFERENCE IN HIGH DIMENSIONAL PANEL MODELS WITH AN APPLICATION TO GUN CONTROL arXiv:1411.6507v1 [stat.ME] 24 NovALEXANDRE BELLONI, VICTOR CHERNOZHUKOV, CHRISTIAN HANSEN, AND DAMIAN KOZBUR

Source URL: arxiv.org

• Statistics
• Regression analysis
• Estimation theory
• Lasso
• Linear regression
• Random effects model
• Least squares
• Fixed effects model
• Ordinary least squares
• Instrumental variable
• Feature selection
• Heteroscedasticity

LUDWIGMAXIMILIANSUNIVERSITY MUNICH DEPARTMENT INSTITUTE FOR INFORMATICS

Source URL: i.cs.hku.hk

• Algebra
• Mathematics
• Statistics
• Cluster analysis
• Data mining
• Geostatistics
• Correlation clustering
• Multivariate statistics
• Eigenvalues and eigenvectors
• Principal component analysis
• Clustering high-dimensional data

CALL FOR PAPER We are pleased to invite you at: Workshop HIGH DIMENSIONAL DATA MINING SIS, CNR and SFdS (group Data Mining and Apprendissage)

Source URL: www.unisa.it

• Formal sciences
• Data
• Knowledge
• Computing
• Software
• Data mining
• Statistica
• Statistics
• Data visualization
• Geographic information system

Large-dimensional factor modeling based on high-frequency observations Markus Pelger∗ August 20, 2015 Abstract

Source URL: www.cb.cityu.edu.hk

• Algebra
• Statistics
• Mathematics
• Multivariate statistics
• Statistical theory
• Estimation theory
• Linear algebra
• Matrix theory
• Eigenvalues and eigenvectors
• Factor analysis
• Spectrum
• Consistent estimator

Semi-Supervised Dimensionality Reduction for Analyzing High-Dimensional Data with Constraints Su Yan∗∗ IBM Almaden Research Center, 650 Harry Rd San Jose, CA 95120, USA Sofien Bouaziz

Source URL: sofienbouaziz.com

• Algebra
• Mathematics
• Statistics
• Multivariate statistics
• Linear algebra
• Functional analysis
• Dimension reduction
• Geostatistics
• Kernel principal component analysis
• Nonlinear dimensionality reduction
• Principal component analysis
• Dimensionality reduction

That was fast! Speeding up NN search of high dimensional distributions.

Source URL: eceweb.ucsd.edu

• Statistics
• Geometry
• Statistical distance
• Estimation theory
• Statistical theory
• Bregman divergence
• Divergence
• Expectationmaximization algorithm
• Exponential family
• KullbackLeibler divergence
• Variational Bayesian methods

On high-dimensional robust regression How to pick the loss in high-dimensional regression? Noureddine El Karoui joint with Bean, Bickel, Lim, Yu Department of Statistics

Source URL: mmds-data.org

• Statistics
• Regression analysis
• Estimation theory
• Statistical theory
• Parametric statistics
• Linear regression
• Robust regression
• Normal distribution
• Degrees of freedom
• Errors and residuals