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Learning Transformations
Qiang Qiu
,
Guillermo Sapiro
Research output
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Chapter in Book/Report/Conference proceeding
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Conference contribution
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Dive into the research topics of 'Learning Transformations'. Together they form a unique fingerprint.
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Keyphrases
Subspace Clustering
100%
Transformation Learning
100%
High-dimensional Data
66%
Low-dimensional Subspace
66%
Linear Transformation
66%
Subspace Classification
66%
Matrix Rank
33%
Clustering Problem
33%
Non-convex Surrogate
33%
Higher Rank
33%
Learning Framework
33%
Image Sequence
33%
Face Image
33%
Rank Structure
33%
Optimization Criterion
33%
Low-rank Structure
33%
Nuclear Norm
33%
Movement Sequence
33%
Intrinsic Structure
33%
Real-world Observation
33%
Low-rank Transformation
33%
Face Movement
33%
Computer Science
High Dimensional Data
100%
Linear Transformation
100%
Dimensional Subspace
100%
Learning Framework
50%
Optimization Criterion
50%
Nuclear Norm
50%
Intrinsic Structure
50%
Mathematics
Dimensional Data
100%
Dimensional Subspace
100%
Linear Transformation
100%
Matrix (Mathematics)
50%
Intrinsic Property
50%