Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Linear Matrix Factorization Embeddings for Single-objective Optimization
  Landscapes   Automated per-instance algorithm selection and configuration have shown
promising performances for a number of classic optimization problems, including
satisfiability, AI planning, and TSP. The techniques often rely on a set of
features that measure some characteristics of the problem instance at hand. In
the context of black-box optimization, these features have to be derived from a
set of $(x,f(x))$ samples. A number of different features have been proposed in
the literature, measuring, for example, the modality, the separability, or the
ruggedness of the instance at hand. Several of the commonly used features,
however, are highly correlated. While state-of-the-art machine learning
techniques can routinely filter such correlations, they hinder explainability
of the derived algorithm design techniques.
  We therefore propose in this work to pre-process the measured (raw) landscape
features through representation learning. More precisely, we show that a linear
dimensionality reduction via matrix factorization significantly contributes
towards a better detection of correlation between different problem instances
-- a key prerequisite for successful automated algorithm design.

27
The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
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The categories of this paper are: stat
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int