Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimization under Uncertainty in the Era of Big Data and Deep Learning:
  When Machine Learning Meets Mathematical Programming   This paper reviews recent advances in the field of optimization under
uncertainty via a modern data lens, highlights key research challenges and
promise of data-driven optimization that organically integrates machine
learning and mathematical programming for decision-making under uncertainty,
and identifies potential research opportunities. A brief review of classical
mathematical programming techniques for hedging against uncertainty is first
presented, along with their wide spectrum of applications in Process Systems
Engineering. A comprehensive review and classification of the relevant
publications on data-driven distributionally robust optimization, data-driven
chance constrained program, data-driven robust optimization, and data-driven
scenario-based optimization is then presented. This paper also identifies
fertile avenues for future research that focuses on a closed-loop data-driven
optimization framework, which allows the feedback from mathematical programming
to machine learning, as well as scenario-based optimization leveraging the
power of deep learning techniques. Perspectives on online learning-based
data-driven multistage optimization with a learning-while-optimizing scheme is
presented.

20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th