Non-negative matrix factorization
Unsupervised Multi Level Non Negative Matrix Factorization Model: Binary Data Case
... in non-negative matrix factorization (NMF) ...base matrix needs to be ...multi-level non-negative matrix factorization model to extract the hidden data ...
6
Blind source separation with optimal transport non negative matrix factorization
... Source separation is the task of separating a mixed signal into different components, usually referred to as sources. In the context of sound processing, it can be used to separate speakers whose voices have been ...
16
hpcNMF: A high-performance toolbox for non-negative matrix factorization
... Non-negative matrix factorization (NMF) is a widely used machine learning algo- rithm for dimension reduction of large-scale data. It has found successful appli- cations in a variety of fields ...
43
Musical instrument classification using non-negative matrix factorization algorithms and subset feature selection
... In this paper, a class of algorithms for automatic classification of individual musical instrument sounds is presented. Sev- eral perceptual features used in sound classification applica- tions as well as MPEG-7 ...
5
Exploring Data Clustering with Non-negative Matrix Factorization Models
... of non-negative matrix factorization (NMF) methods for various clustering ...two non-negative matrix whose product approximates the original ...The non- negativity ...
104
Iterative Weighted Non-smooth Non-negative Matrix Factorization for Face Recognition
... data matrix and reconstruction ...labels. Non-negative matrix factorization (NMF) is applied over data distribution for linear discriminant analysis which achieves good results ...
10
Non Negative Matrix Factorization Based UKF Algorithm for Constant Modulus Signals in Adaptive Beamforming
... Blind adaptive beamforming is getting appreciated for its various applications in contemporary communication systems where sources are statistically dependent or independent that are allowed to formulate new algorithms. ...
10
A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization
... Bayesian Non-negative Matrix Factorization (BNMF) is a promising approach for under- standing uncertainty and structure in matrix ...traditional non-Bayesian NMF objectives that ...
56
Robust Non Blind Colour Image Watermarking Using Non Negative Matrix Factorization Technique in DWT Domain
... Abstract:- A robust colour image watermarking scheme for copyright protection using a Non-negative Matrix Factorization (NMF) in Discrete Wavelet Transform (DWT) domain is suggested. The main ...
10
Reduction of Non stationary Noise for a Robotic Living Assistant using Sparse Non negative Matrix Factorization
... Non-negative Matrix Factorization (NMF) is an approach introduced by Lee & Seung (Lee and Se- ung, 2001) in which the data is described as the product of a set of basis and of a set of ...
6
Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization
... 1 Non-negative matrix factorization (NMF) learns a parts-based representation of faces, whereas vector quantization (VQ) and principal components analysis (PCA) learn holistic ...m ...
140
Mapping Question Items to Skills with Non-negative Matrix Factorization
... on Non-negative Matrix Factorization (NMF) was shown to offer valuable results, especially due to the fact that the resulting factor- ization allows a straightforward interpretation in terms ...
7
Sparse Non negative Matrix Factorization and its Application in Overlapped Chromatograms Separation
... Lee and Seung Suggested Non-negative Matrix Factorization (NMF) in 1999 [13] and provided more algorithms in 2001 [14]. It has been generally applied to image and text data mining. Several ...
10
Clustering Student Discussion Messages on Online Forumby Visualization and Non Negative Matrix Factorization
... apply non-negative matrix factorization and visualization to clustering message data, in order to provide a summary view of messages that disclose their deep semantic ...
6
Percussive/harmonic sound separation by non-negative matrix factorization with smoothness/sparseness constraints
... monaural non-vocal polyphonic signals. Our algorithm is based on a modified non-negative matrix factorization (NMF) procedure that no labeled data is required to distinguish between ...
17
Testing supervised classifiers based on non-negative matrix factorization to musical instrument classification
... In this paper, a class of algorithms for automatic classifica- tion of individual musical instrument sounds is presented. Two feature sets were employed, the first containing percep- tual features and MPEG-7 descriptors ...
6
Posteriori Regularization based Non Negative Matrix Factorization approach for Speech Enhancement
... Abstract: The paper proposes, a speech enhancement method for reducing additive Gaussian noise using iterative posterior regularized Non-negative matrix factorization (NMF). Here, ...
6
Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
... 1994), non-negative matrix factorization (NMF) has become increasingly popular for feature extraction in machine learning, computer vision, and signal processing ...than non-sparse, ...
23
Applying supervised classifiers based on non-negative matrix factorization to musical instrument classification
... In this paper, a new approach for automatic audio classification us- ing non-negative matrix factorization (NMF) is presented. Training is performed onto each audio class individually, whilst ...
5
Feature enhancement of reverberant speech by distribution matching and non negative matrix factorization
... years—non-negative matrix factorization (NMF)—which models the speech spectrogram as a sparse non-negative linear combination of dictionary elements (“speech ...NMF, ...
14