Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributionally Robust Learning with Stable Adversarial Training   Machine learning algorithms with empirical risk minimization are vulnerable
under distributional shifts due to the greedy adoption of all the correlations
found in training data. There is an emerging literature on tackling this
problem by minimizing the worst-case risk over an uncertainty set. However,
existing methods mostly construct ambiguity sets by treating all variables
equally regardless of the stability of their correlations with the target,
resulting in the overwhelmingly-large uncertainty set and low confidence of the
learner. In this paper, we propose a novel Stable Adversarial Learning (SAL)
algorithm that leverages heterogeneous data sources to construct a more
practical uncertainty set and conduct differentiated robustness optimization,
where covariates are differentiated according to the stability of their
correlations with the target. We theoretically show that our method is
tractable for stochastic gradient-based optimization and provide the
performance guarantees for our method. Empirical studies on both simulation and
real datasets validate the effectiveness of our method in terms of uniformly
good performance across unknown distributional shifts.

25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th