Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Branch & Learn for Recursively and Iteratively Solvable Problems in
  Predict+Optimize   This paper proposes Branch & Learn, a framework for Predict+Optimize to
tackle optimization problems containing parameters that are unknown at the time
of solving. Given an optimization problem solvable by a recursive algorithm
satisfying simple conditions, we show how a corresponding learning algorithm
can be constructed directly and methodically from the recursive algorithm. Our
framework applies also to iterative algorithms by viewing them as a degenerate
form of recursion. Extensive experimentation shows better performance for our
proposal over classical and state-of-the-art approaches.

36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th