Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Foundations of a Multi-way Spectral Clustering Framework for Hybrid
  Linear Modeling   The problem of Hybrid Linear Modeling (HLM) is to model and segment data
using a mixture of affine subspaces. Different strategies have been proposed to
solve this problem, however, rigorous analysis justifying their performance is
missing. This paper suggests the Theoretical Spectral Curvature Clustering
(TSCC) algorithm for solving the HLM problem, and provides careful analysis to
justify it. The TSCC algorithm is practically a combination of Govindu's
multi-way spectral clustering framework (CVPR 2005) and Ng et al.'s spectral
clustering algorithm (NIPS 2001). The main result of this paper states that if
the given data is sampled from a mixture of distributions concentrated around
affine subspaces, then with high sampling probability the TSCC algorithm
segments well the different underlying clusters. The goodness of clustering
depends on the within-cluster errors, the between-clusters interaction, and a
tuning parameter applied by TSCC. The proof also provides new insights for the
analysis of Ng et al. (NIPS 2001).

28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas