Learning the parts of objects by non-negative matrix factorization
Daniel D. Lee, H. Sebastian Seung
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- Machine Learning in Medicine→Learning the parts of objects by non-negative matrix factorizationLegacy edge — source detail unavailable
- From Frequency to Meaning: Vector Space Models of Semantics→Learning the parts of objects by non-negative matrix factorizationLegacy edge — source detail unavailable
- Slice sampling→Learning the parts of objects by non-negative matrix factorizationLegacy edge — source detail unavailable
- Learning the parts of objects by non-negative matrix factorization→A solution to Plato's problem: The latent semantic analysis theory of acquisition, induct…Legacy edge — source detail unavailable
- Learning the parts of objects by non-negative matrix factorization→The Handbook of brain theory and neural networksLegacy edge — source detail unavailable
- Learning the parts of objects by non-negative matrix factorization→An iterative technique for the rectification of observed distributionsLegacy edge — source detail unavailable
- From Frequency to Meaning: Vector Space Models of Semantics→A solution to Plato's problem: The latent semantic analysis theory of acquisition, induct…Legacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Machine Learning in Medicine | 2015 | 3,534 |
| From Frequency to Meaning: Vector Space Models of Semantics | 2010 | 2,902 |
| Slice sampling | 2003 | 1,367 |
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Topics
| Neural Networks and Applications | Computer Science |
| Face Recognition and Perception | Neuroscience |
| Image Retrieval and Classification Techniques | Computer Science |
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