Grassmann Clustering

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n(t) s(t) � A F. Theis x(t) Aim of my talk • clustering - elementary concept of machine learning • review and illustrate simple clustering algorithm • extend it to more general metric spaces • projective space • Grassmann manifolds • general submanifolds (via kernels) • applications (very brief - work in progress) • ICA, NMF • approximate combinatorial convex optimization 2 Apr 6, 2006 :: Tübingen
n(t) s(t) � A F. Theis x(t) I. Introduction Agenda II. Partitional Clustering III. Projective Clustering IV. Grassmann Clustering V. Subspace Clustering 3 Apr 6, 2006 :: Tübingen
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Grassmann Clustering

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