A Unified Framework for Sparse Non-Negative Least Squares using Multiplicative Updates and the Non-Negative Matrix Factorization Problem

no code implementations • 7 Apr 2016 • Igor Fedorov, Alican Nalci, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen, Harinath Garudadri

We show that the proposed framework encompasses a large class of S-NNLS algorithms and provide a computationally efficient inference procedure based on multiplicative update rules.

Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem

no code implementations • 22 Jan 2016 • Alican Nalci, Igor Fedorov, Maher Al-Shoukairi, Thomas T. Liu, Bhaskar D. Rao

We refer to the proposed method as rectified sparse Bayesian learning (R-SBL).