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Sparse dictionary learning

Sparse dictionary learning is a representation learning method which aims at finding a sparse representation of the input data (also known as sparse… 
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Related topics

Related topics

27 relations
Audio signal processingAutoencoderBasis (linear algebra)Conjugate gradient method

Broader (1)

Machine learning

Papers overview

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2019
2019
Secure Dictionary Learning for Sparse Representation
In this paper, we propose secure dictionary learning for sparse representation based on a random unitary transform. Edge cloud… 
2018
2018
Blood Cell Detection and Counting Using Convolutional Sparse Dictionary Learning
Blood count identification has been analyzed for all types of blood which are useful in clinical purpose. During early 1950… 
2018
2018
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning
Sparse dictionary learning (SDL) has become a popular method for learning parsimonious representations of data, a fundamental… 
2017
2017
On the Reconstruction Risk of Convolutional Sparse Dictionary Learning
Sparse dictionary learning (SDL) has become a popular method for adaptively identifying parsimonious representations of a dataset… 
2014
2014
Sparse dictionary learning from 1-BIT data
This work examines a sparse dictionary learning task - that of fitting a collection of data points, arranged as columns of a… 
2014
2014
Joint DOA and multi-pitch estimation via block sparse dictionary learning
In this paper, we introduce a novel sparse method for joint estimation of the direction of arrivals (DOAs) and pitches of a set… 
2014
2014
Sparse prediction for compression of stereo color images conditional on constant disparity patches
This paper introduces an algorithm for lossless encoding of color stereo images using sparse prediction and context coding. For… 
2013
2013
Group sparse dictionary learning and inference for resting-state fMRI analysis of Alzheimer'S disease
A novel group analysis tool for data-driven resting state fMRI analysis using group sparse dictionary learning and mixed model is… 
2012
2012
Large-scale distributed non-negative sparse coding and sparse dictionary learning
We consider the problem of building compact, unsupervised representations of large, high-dimensional, non-negative data using… 
2011
2011
Pattern selection approaches for the logical analysis of data considering the outliers and the coverage of a pattern
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