In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitti...
Junzhou Huang, Shaoting Zhang, Dimitris N. Metaxas
In this paper a novel approach for semi-supervised hyperspectral unmixing is presented. First, it is shown that this problem inherently accepts a sparse solution. Then, based on t...
Konstantinos Themelis, Athanasios A. Rontogiannis,...
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...