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Using underapproximations for sparse nonnegative matrix factorization
GILLIS, Nicolas; GLINEUR, François - Center for Operations Research and Econometrics (CORE), … - 2009
Nonnegative Matrix Factorization (NMF) has gathered a lot of attention in the last decade and has been successfully applied in numerous applications. It consists in the factorization of a nonnegative matrix by the product of two low-rank nonnegative matrices:. MªVW. In this paper, we attempt to...
Persistent link: https://www.econbiz.de/10008550194
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Relational analysis model of weather conditions and sales patterns based on nonnegative tensor factorization
Okayama, Sei; Yamashita, Haruka; Mikawa, Kenta; Goto, … - In: International journal of production research 58 (2020) 8, pp. 2477-2489
Persistent link: https://www.econbiz.de/10012265244
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Global convergence of modified multiplicative updates for nonnegative matrix factorization
Takahashi, Norikazu; Hibi, Ryota - In: Computational Optimization and Applications 57 (2014) 2, pp. 417-440
problem. Furthermore, we propose algorithms based on the modified updates that always stop within a finite number of …
Persistent link: https://www.econbiz.de/10010847448
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Heuristics for exact nonnegative matrix factorization
Gillis, Nicolas; Glineur, François; Tuyttens, Daniel; … - Center for Operations Research and Econometrics (CORE), … - 2015
The exact nonnegative matrix factorization (exact NMF) problem is the following: given an m-by-n nonnegative matrix X and a factorization rank r, find, if possible, an m-by-r nonnegative matrix W and an r-by-n nonnegative matrix H such that X = WH. In this paper, we propose two heuristics for...
Persistent link: https://www.econbiz.de/10011246293
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Nested nonnegative cone analysis
Zhang, Lingsong; Lu, Shu; Marron, J.S. - In: Computational Statistics & Data Analysis 88 (2015) C, pp. 100-110
Motivated by the analysis of nonnegative data objects, a novel Nested Nonnegative Cone Analysis (NNCA) approach is proposed to overcome some drawbacks of existing methods. The application of traditional PCA/SVD method to nonnegative data often cause the approximation matrix leave the nonnegative...
Persistent link: https://www.econbiz.de/10011264466
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Nonnegative factorization and the maximum edge biclique problem
GILLIS, Nicolas; GLINEUR, François - Center for Operations Research and Econometrics (CORE), … - 2008
updates to NF, which allows us to shed some light on the differences between the MU and HALS algorithms for NMF and give an …
Persistent link: https://www.econbiz.de/10005008154
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Semi-supervised clustering algorithm for community structure detection in complex networks
Ma, Xiaoke; Gao, Lin; Yong, Xuerong; Fu, Lidong - In: Physica A: Statistical Mechanics and its Applications 389 (2010) 1, pp. 187-197
so-called SNMF-SS, by combining SNMF and a semi-supervised clustering approach. Previous NMF-based algorithms often …
Persistent link: https://www.econbiz.de/10010590435
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Nonnegative factorization and the maximum edge biclique problem
GILLIS, Nicolas; GLINEUR, François - Center for Operations Research and Econometrics (CORE), … - 2010
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 case of rank-one factorization and show...
Persistent link: https://www.econbiz.de/10008836155
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Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework
Kim, Jingu; He, Yunlong; Park, Haesun - In: Journal of Global Optimization 58 (2014) 2, pp. 285-319
We review algorithms developed for nonnegative matrix factorization (NMF) and nonnegative tensor factorization (NTF … NMF and NTF algorithms, which are consistent with experimental observations reported in literature. In addition, we … discuss algorithms that do not fit in the BCD framework contrasting them from those based on the BCD framework. With insights …
Persistent link: https://www.econbiz.de/10010896402
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Jump-preserving monitoring of dependent time series using pilot estimators
Steland, Ansgar - 2003
An important problem of the statistical analysis of time series is to detect change-points in the mean structure. Since this problem is a one-dimensional version of the higher dimensional problem of detecting edges in images, we study detection rules which benefit from results obtained in image...
Persistent link: https://www.econbiz.de/10010306257