SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions.
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ABSTRACT:
SUBMITTER: Bajaj C
PROVIDER: S-EPMC7394310 | biostudies-literature | 2018 Jul
REPOSITORIES: biostudies-literature
Publications
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions.
Bajaj Chandrajit C Gao Tingran T He Zihang Z Huang Qixing Q Liang Zhenxiao Z
Proceedings of machine learning research 20180701
We introduce a principled approach for <i>simultaneous mapping and clustering</i> (SMAC) for establishing consistent maps across heterogeneous object collections (e.g., 2D images or 3D shapes). Our approach takes as input a heterogeneous object collection and a set of maps computed between some pairs of objects, and outputs a homogeneous object clustering together with a new set of maps possessing optimal intra- and inter-cluster consistency. Our approach is based on the spectral decomposition o ...[more]
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