Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Interpretable Clustering via Multi-Polytope Machines   Clustering is a popular unsupervised learning tool often used to discover
groups within a larger population such as customer segments, or patient
subtypes. However, despite its use as a tool for subgroup discovery and
description - few state-of-the-art algorithms provide any rationale or
description behind the clusters found. We propose a novel approach for
interpretable clustering that both clusters data points and constructs
polytopes around the discovered clusters to explain them. Our framework allows
for additional constraints on the polytopes - including ensuring that the
hyperplanes constructing the polytope are axis-parallel or sparse with integer
coefficients. We formulate the problem of constructing clusters via polytopes
as a Mixed-Integer Non-Linear Program (MINLP). To solve our formulation we
propose a two phase approach where we first initialize clusters and polytopes
using alternating minimization, and then use coordinate descent to boost
clustering performance. We benchmark our approach on a suite of synthetic and
real world clustering problems, where our algorithm outperforms state of the
art interpretable and non-interpretable clustering algorithms.

28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin