Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Feature Selection in High-dimensional Space Using Graph-Based Methods   High-dimensional feature selection is a central problem in a variety of
application domains such as machine learning, image analysis, and genomics. In
this paper, we propose graph-based tests as a useful basis for feature
selection. We describe an algorithm for selecting informative features in
high-dimensional data, where each observation comes from one of $K$ different
distributions. Our algorithm can be applied in a completely nonparametric setup
without any distributional assumptions on the data, and it aims at outputting
those features in the data, that contribute the most to the overall
distributional variation. At the heart of our method is the recursive
application of distribution-free graph-based tests on subsets of the feature
set, located at different depths of a hierarchical clustering tree constructed
from the data. Our algorithm recovers all truly contributing features with high
probability, while ensuring optimal control on false-discovery. Finally, we
show the superior performance of our method over other existing ones through
synthetic data, and also demonstrate the utility of the method on a real-life
dataset from the domain of climate change.

34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph