We propose an unsupervised inference procedure for audio source separation. Components in nonnegative matrix factorization (NMF) are grouped automatically in audio sources via a p...
This article deals with a regularized version of the split gradient method (SGM), leading to multiplicative algorithms. The proposed algorithm is available for the optimization of...
While nonnegative matrix factorization (NMF) has successfully been applied for gain-robust multi-pitch detection, a method to track pitch values over time was not provided. We emb...
This paper introduces a novel algorithm for the nonnegative matrix factorization and completion problem, which aims to find nonnegative matrices X and Y from a subset of entries o...
In this paper, we restudy the non-convex data factorization problems (regularized or not, unsupervised or supervised), where the optimization is confined in the nonnegative orthan...
Nonnegative matrix factorization (NMF) is a widely-used method for low-rank approximation (LRA) of a nonnegative matrix (matrix with only nonnegative entries), where nonnegativity...
The recent years have witnessed a surge of interests in Nonnegative Matrix Factorization (NMF) in data mining and machine learning fields. Despite its elegant theory and empirical...
—This study examines the ability of nonnegative matrix factorization (NMF) as a method for constructing semantic spaces, in which the meaning of each word is represented by a hig...
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...
We introduce the posterior probabilistic clustering (PPC), which provides a rigorous posterior probability interpretation for Nonnegative Matrix Factorization (NMF) and removes th...