Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
—We document methods for the quantitative evaluation of systems that produce a scalar summary of a biometric sample’s quality. We are motivated by a need to test claims that qu...
This work presents a new comparison-based diagnosis model and a new algorithm, called Hi-Dif, based on this model. The algorithm is used for checking the integrity of systems with...
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...