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~subject:"PCA with missing data"
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PCA with missing data
Global optimization
2
Block coordinate descent
1
Blow-up
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Cadzow iterations
1
Cointegration
1
Differential equations
1
Dynamical low-rank approximation
1
Estimation theory
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Hankel matrix
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Hankel operator
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Image compression
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Information retrieval
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Kointegration
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Latent Semantic Indexing
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Latent semantic indexing
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Local power
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Low rank approximation
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Low-rank approximation
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Low-rank approximation methods
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Misspecification
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Model reduction
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Nonnegative matrix factorization
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Nonnegative tensor factorization
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Null space estimation
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Plug-in principle
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Ranking method
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Ranking-Verfahren
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Reduced-rank approximation
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Schätztheorie
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Semi-infinite matrix
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Singular Value Decomposition
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Singular spectrum analysis
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Statistical test
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Statistischer Test
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Structured low rank approximation
1
Tensor approximation
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Tests of rank
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Time series
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Vandermonde factorization
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GILLIS, Nicolas
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GLINEUR, François
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Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain
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Low-rank matrix approximation with weights or missing data is NP-hard
GILLIS, Nicolas
;
GLINEUR, François
-
Center for Operations Research and Econometrics (CORE), …
-
2010
Weighted low-
rank
approximation
(WLRA), a dimensionality reduction technique for data analysis, has been successfully …
Persistent link: https://www.econbiz.de/10008836126
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