Link prediction based on non-negative matrix factorization. [PDF]
PLoS ONE, 2017 With the rapid expansion of internet, the complex networks has become high-dimensional, sparse and redundant. Besides, the problem of link prediction in such networks has also obatined increasingly attention from different types of domains like ...
Bolun Chen +4 more
doaj +1 more source
Unsupervised learning of overlapping image components using divisive input modulation [PDF]
, 2009 This paper demonstrates that nonnegative matrix factorisation is mathematically related to a class of neural networks that employ negative feedback as a mechanism of competition. This observation inspires a novel learning algorithm which we call Divisive
De Meyer, Kris +5 more
core +1 more source
On the Complexity of the Paper Selection Problem for the Italian Research Quality Evaluation (VQR)
Networks, EarlyView.ABSTRACT This work addresses the paper selection problem that each Italian university and department faced in the context of the research quality evaluation (VQR) of the Italian university system for the period 2020–2024. Given the set of researchers of a university and their associated papers, the problem consists of selecting a fixed number of ...
Francesco Carrabs +2 more
wiley +1 more source
Face Recognition Based on Wavelet Kernel Non-Negative Matrix Factorization
Cybernetics and Information Technologies, 2014 In this paper a novel face recognition algorithm, based on wavelet kernel non-negative matrix factorization (WKNMF), is proposed. By utilizing features from multi-resolution analysis, the nonlinear mapping capability of kernel nonnegative matrix ...
Bai, Lin, Li Yanbo, Hui Meng
doaj +1 more source
Using underapproximations for sparse nonnegative matrix factorization [PDF]
Nonnegative Matrix Factorization (NMF) has gathered a lot of attention in the last decade and has been successfully applied in numerous applications.
GILLIS, Nicolas, GLINEUR, François
core
Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets [PDF]
, 2016 Nonnegative Matrix Factorization (NMF) with Kullback-Leibler Divergence (NMF-KL) is one of the most significant NMF problems and equivalent to Probabilistic Latent Semantic Indexing (PLSI), which has been successfully applied in many applications.
Ho, Tu-Bao, Nguyen, Duy-Khuong
core +1 more source
Statistical Monitoring of Multivariate Count Data From Real‐Time Particle Counters
Quality and Reliability Engineering International, EarlyView.ABSTRACT In the pharmaceutical industry, production environments are monitored for bacterial contamination. Particle counters are increasingly investigated for real‐time monitoring of viable microorganisms using count data for different particle size intervals.
Mona Emampour +2 more
wiley +1 more source
Nonnegative factorization and the maximum edge biclique problem [PDF]
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix with a product of two nonnegative factors, which allows compression and interpretation of nonnegative data. In this paper, we study the
GILLIS, Nicolas, GLINEUR, François
core
A differentially private nonnegative matrix factorization for recommender system
, 2022 Nonnegative matrix factorization (NMF)-based models have been proven to be highly effective and scalable in addressing collaborative filtering (CF) problems in the recommender system (RS).
Ran, Xun +3 more
core +1 more source
Control Design Based on Generalized Lur'e Lyapunov Functions for Sampled‐Data Lur'e Systems
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT This article addresses the synthesis of stabilizing control laws for aperiodic sampled‐data Lur'e systems. Based on a hybrid system representation of the closed‐loop system and a timer‐dependent generalized Lur'e–Postnikov type Lyapunov function, stabilization conditions are obtained by separating decision variables with the application of two
Arthur Scolari Fagundes +2 more
wiley +1 more source