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Algorithms for non-negative matrix factorization

D Seung, +1 more
- Vol. 13, pp 556-562
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The article was published on 2001-01-01 and is currently open access. It has received 5015 citations till now. The article focuses on the topics: Non-negative matrix factorization.

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Journal ArticleDOI

Evolutionary Network Analysis: A Survey

TL;DR: This survey provides an overview of the vast literature on graph evolution analysis and the numerous applications that arise in different contexts.
Journal ArticleDOI

On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing

TL;DR: It is shown that PLSI and NMF (with the I-divergence objective function) optimize the same objective function, although PLSi andNMF are different algorithms as verified by experiments.
Journal ArticleDOI

Discriminant Locally Linear Embedding With High-Order Tensor Data

TL;DR: This work proposes a new manifold learning technique called discriminant locally linear embedding (DLLE), in which the local geometric properties within each class are preserved according to the locally linear embeddedding (LLE) criterion, and the separability between different classes is enforced by maximizing margins between point pairs on different classes.
Journal ArticleDOI

Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image

TL;DR: A novel gradient-based learning algorithm is proposed for finding the optimal set of local linear bases for multiclass nonlinear discrimination and it is computationally highly efficient as compared to GDA.
Proceedings ArticleDOI

Relation between PLSA and NMF and implications

TL;DR: It is shown that PLSA solves the problem of NMF with KL divergence, and the implications of this relationship are explored.
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