Difference between revisions of "paper Summaries"
From statwiki
(→Set B) 
m (Conversion script moved page Paper Summaries to paper Summaries: Converting page titles to lowercase) 
(No difference)

Latest revision as of 09:45, 30 August 2017
Contents
 1 Set A
 1.1 A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
 1.2 DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
 1.3 A Direct Formulation For Sparse PCA Using Semidefinite Programming
 1.4 Compressive Sensing
 1.5 Deflation Methods for Sparse PCA
 1.6 Supervised Dictionary Learning
 1.7 Matrix Completion with Noise
 1.8 SelfTaught_Learning
 1.9 Uncovering Shared Structures in Multiclass Classification
 1.10 A Rank Minimization Heuristic with Application to Minimum Order System Approximation
 1.11 Compressive Sensing (Candes)
 2 Set B
 2.1 MultiTask Feature Learning
 2.2 Probabilistic Matrix Factorization
 2.3 Probabilistic PCA with Gaussian Process Latent Variable Models
 2.4 Consistency of Trace Norm Minimization
 2.5 Optimal Solutions forSparse Principal Component Analysis
 2.6 A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
Set A
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
SelfTaught_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
Compressive Sensing (Candes)
Compressive Sensing by Candes et al.
Set B
MultiTask Feature Learning
Probabilistic Matrix Factorization
Probabilistic Matrix Factorization
Probabilistic PCA with Gaussian Process Latent Variable Models
Probabilistic Principle Component Analysis with Gaussian Process Latent Variable Models
Consistency of Trace Norm Minimization
Consistency of Trace Norm Minimization
Optimal Solutions forSparse Principal Component Analysis
Optimal Solutions forSparse Principal Component Analysis
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization