Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ecole: A Library for Learning Inside MILP Solvers   In this paper we describe Ecole (Extensible Combinatorial Optimization
Learning Environments), a library to facilitate integration of machine learning
in combinatorial optimization solvers. It exposes sequential decision making
that must be performed in the process of solving as Markov decision processes.
This means that, rather than trying to predict solutions to combinatorial
optimization problems directly, Ecole allows machine learning to work in
cooperation with a state-of-the-art a mixed-integer linear programming solver
that acts as a controllable algorithm. Ecole provides a collection of
computationally efficient, ready to use learning environments, which are also
easy to extend to define novel training tasks. Documentation and code can be
found at https://www.ecole.ai.

30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
7
The categories of this paper are: hep-th
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat