The nonnegative matrix factorization (NMF) has been shown recently to be useful for clustering. Various extensions of NMF have also been proposed. In this paper we present an over...
In the paper we present new Alternating Least Squares (ALS) algorithms for Nonnegative Matrix Factorization (NMF) and their extensions to 3D Nonnegative Tensor Factorization (NTF) ...
Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF`s batch nature necessitates recomputation of whole basis set for new samples...
Nonnegative matrix factorization (NMF) is a versatile model for data clustering. In this paper, we propose several NMF inspired algorithms to solve different data mining problems....
We present a technique for denoising speech using nonnegative matrix factorization (NMF) in combination with statistical speech and noise models. We compare our new technique to s...
Kevin W. Wilson, Bhiksha Raj, Paris Smaragdis, Aja...
Sight-reading is the ability to read and perform music from a written score with little or no preparation. Though an integral part of musicianship, it is rarely or minimally addre...
Chih-Chieh Cheng, D. Jingtong Hu, Lawrence K. Saul
Nonnegative Tucker decomposition (NTD) is a recent multiway extension of nonnegative matrix factorization (NMF), where nonnegativity constraints are incorporated into Tucker model...
There has been much recent progress in the technical infrastructure necessary to continuously characterize and archive all sounds, or more precisely auditory streams, that occur w...
Jiachen Xue, Gordon Wichern, Harvey D. Thornburg, ...
The Web abounds with dyadic data that keeps increasing by every single second. Previous work has repeatedly shown the usefulness of extracting the interaction structure inside dya...
Large 0-1 datasets arise in various applications, such as market basket analysis and information retrieval. We concentrate on the study of topic models, aiming at results which in...