Big Data Covariance Estimation

Abstract

The research aims at contributing to the development of statistical methods for the analysis of big data. It developed along two lines. On one side it addressed the issue of large covariance estimation based on the assumption that the covariance matrix can be decomposed into the sum of a low rank and a sparse component.

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Document Details

Document Type
Technical Report
Publication Date
Apr 20, 2020
Accession Number
AD1106499

Entities

People

  • Angela Montanari

Organizations

  • University of Bologna

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Data Analysis
  • Data Curation
  • Data Mining
  • Data Science
  • Databases
  • Dimensionality Reduction
  • Factor Analysis
  • Information Processing
  • Information Science
  • Machine Learning
  • Network Science
  • Statistical Algorithms
  • Statistics
  • Surveys
  • Unsupervised Machine Learning

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Linear Algebra
  • Statistical inference.