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Matrix regularization

Known as: Regularization 
In the field of statistical learning theory, matrix regularization generalizes notions of vector regularization to cases where the object to be… 
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Related topics

Related topics

9 relations

Broader (2)

Estimation theoryMachine learning
Laplacian matrixMatching pursuitMulti-task learningMultiple kernel learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2012
Highly Cited
2012
Model sparsity and brain pattern interpretation of classification models in neuroimaging
Highly Cited
2011
Highly Cited
2011
A new investigation into regularization techniques for the method of fundamental solutions
Highly Cited
2009
Highly Cited
2009
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation
Motivated from real world problems, like object categorization, we study a particular mixed-norm regularization for Multiple… 
Highly Cited
2009
Highly Cited
2009
Alternating Projections for Learning with Expectation Constraints
We present an objective function for learning with unlabeled data that utilizes auxiliary expectation constraints. We optimize… 
Highly Cited
2007
Highly Cited
2007
A Fast Algorithm for Image Deblurring with Total Variation Regularization
We propose and test a simple algorithmic framework for recovering images from blurry and noisy observations based on total… 
Highly Cited
2007
Highly Cited
2007
On the Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional
In region-based image segmentation, two models dominate the field: the Mumford-Shah functional and statistical approaches based… 
Highly Cited
2005
Highly Cited
2005
A direct finite element implementation of the gradient‐dependent theory
The enhanced non‐local gradient‐dependent theories formulate a constitutive framework on the continuum level that is used to… 
Highly Cited
2002
Highly Cited
2002
Regularization and statistical learning theory for data analysis
Highly Cited
2001
Highly Cited
2001
A general method to devise maximum-likelihood signal restoration multiplicative algorithms with non-negativity constraints
Highly Cited
1995
Highly Cited
1995
Learning methodology for failure detection and accommodation
A major goal of intelligent control systems is to achieve high performance with increased reliability, availability, and… 
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