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Maggu et al., 2023 - Google Patents

Kernelized transformed subspace clustering with geometric weights for non-linear manifolds

Maggu et al., 2023

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Document ID
3388332701992290363
Author
Maggu J
Majumdar A
Publication year
Publication venue
Neurocomputing

External Links

Snippet

The naive assumption of subspace clustering is that the data should be separable into separate subspaces. Another consideration of the conventional subspace clustering methods is the linear manifolds. What if, the data doesn't hold this assumption? We propose …
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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
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