Tables are an abundant form of data with use cases across all scientific...
The paper presents an image denoising scheme by combining a method that ...
When presented with a binary classification problem where the data exhib...
A novel artificial intelligence (AI) technique that uses machine learnin...
Canonical Correlation Analysis (CCA) models can extract informative
corr...
The paper presents a versatile library of quasi-analytic complex-valued
...
The paper presents a versatile library of analytic and quasi-analytic
co...
This paper provides a new similarity detection algorithm. Given an input...
High-dimensional big data appears in many research fields such as image
...
The input data features set for many data driven tasks is high-dimension...
Manifold learning methods are useful for high dimensional data analysis....
Diffusion Maps framework is a kernel based method for manifold learning ...
Dimensionality reduction methods are very common in the field of high
di...
In this study we consider learning a reduced dimensionality representati...
In recent years, distinctive-dictionary construction has gained importan...
Identifying moving objects in a video sequence, which is produced by a s...
We describe several algorithms for matrix completion and matrix approxim...