AI RESEARCH
Flexible Online Representation Learning Based on Similarity Matching
arXiv CS.LG
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ArXi:2606.01546v1 Announce Type: new Sparse high-dimensional representations are conducive to uncovering nontrivial structures in unsupervised exploration of data. Such a representation can deal with the dense connectivity in graphs relevant to community detection problems. However, sparse high-dimensional representations are capable of doing more, including manifold tiling and feature learning.