Some computational problems in data mining applications
In this INFORMAL talk I'll survey several recent advances in data
clustering and dimension reduction, discussing contributions both
from my own research and others: 1) graph partitioning for data clustering
using spectral relaxation; 2) probabilistic latent semantic indexing;
and 3) spectral methods for finding intrinsic dimensions of data
manifolds.
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