Dictionary Learning

151 papers with code • 0 benchmarks • 6 datasets

Dictionary Learning is an important problem in multiple areas, ranging from computational neuroscience, machine learning, to computer vision and image processing. The general goal is to find a good basis for given data. More formally, in the Dictionary Learning problem, also known as sparse coding, we are given samples of a random vector $y\in\mathbb{R}^n$, of the form $y=Ax$ where $A$ is some unknown matrix in $\mathbb{R}^{n×m}$, called dictionary, and $x$ is sampled from an unknown distribution over sparse vectors. The goal is to approximately recover the dictionary $A$.

Source: Polynomial-time tensor decompositions with sum-of-squares

Libraries

Use these libraries to find Dictionary Learning models and implementations

Most implemented papers

Fast Low-rank Shared Dictionary Learning for Image Classification

tiepvupsu/DICTOL 27 Oct 2016

Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries.

Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning

matthieuheitz/WassersteinDictionaryLearning 7 Aug 2017

Wasserstein barycenters) between dictionary atoms; such atoms are themselves synthetic histograms in the probability simplex.

Multi-focus Image Fusion using dictionary learning and Low-Rank Representation

exceptionLi/imagefusion_dllrr 23 Apr 2018

In this paper, we propose a novel multi-focus image fusion method based on dictionary learning and LRR to get a better performance in both global and local structure.

Greedy Frank-Wolfe Algorithm for Exemplar Selection

garyxcheng/FWSR 6 Nov 2018

In this paper, we consider the problem of selecting representatives from a data set for arbitrary supervised/unsupervised learning tasks.

CASTER: Predicting Drug Interactions with Chemical Substructure Representation

kexinhuang12345/CASTER 15 Nov 2019

Adverse drug-drug interactions (DDIs) remain a leading cause of morbidity and mortality.

COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF

HanbaekLyu/ONMF-COVID19 20 Apr 2020

One of the main sources of difficulty is that a very limited amount of daily COVID-19 case data is available, and with few exceptions, the majority of countries are currently in the "exponential spread stage," and thus there is scarce information available which would enable one to predict the phase transition between spread and containment.

Semi-supervised dictionary learning with graph regularization and active points

ktran1/SSDL 13 Sep 2020

Supervised Dictionary Learning has gained much interest in the recent decade and has shown significant performance improvements in image classification.

Learning Multiscale Convolutional Dictionaries for Image Reconstruction

liutianlin0121/musc 25 Nov 2020

To close the performance gap, we thus propose a multiscale convolutional dictionary structure.

Learning low-rank latent mesoscale structures in networks

HanbaekLyu/NDL_paper 13 Feb 2021

It is common to use networks to encode the architecture of interactions between entities in complex systems in the physical, biological, social, and information sciences.

Blind Primed Supervised (BLIPS) Learning for MR Image Reconstruction

sjames40/multi_coil_local_model 11 Apr 2021

We also compare the proposed method to alternative approaches for combining dictionary-based methods with supervised learning in MR image reconstruction.