# Difference between revisions of "paper Summaries"

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+ | ==A Rank Minimization Heuristic with Application to Minimum Order System Approximation== | ||

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## Revision as of 19:55, 23 November 2010

## Contents

- 1 A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
- 2 DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
- 3 A Direct Formulation For Sparse PCA Using Semidefinite Programming
- 4 Compressive Sensing
- 5 Deflation Methods for Sparse PCA
- 6 Supervised Dictionary Learning
- 7 Matrix Completion with Noise
- 8 Self-Taught_Learning
- 9 Uncovering Shared Structures in Multiclass Classification
- 10 A Rank Minimization Heuristic with Application to Minimum Order System Approximation

## A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis

## DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification

DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification

## A Direct Formulation For Sparse PCA Using Semidefinite Programming

A Direct Formulation For Sparse PCA Using Semidefinite Programming

## Compressive Sensing

## Deflation Methods for Sparse PCA

Deflation Methods for Sparse PCA

## Supervised Dictionary Learning

Supervised Dictionary Learning

## Matrix Completion with Noise

## Self-Taught_Learning

Uncovering Shared Structures in Multiclass Classification

## A Rank Minimization Heuristic with Application to Minimum Order System Approximation

A Rank Minimization Heuristic with Application to Minimum Order System Approximation