Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust Regression for Safe Exploration in Control   We study the problem of safe learning and exploration in sequential control
problems. The goal is to safely collect data samples from operating in an
environment, in order to learn to achieve a challenging control goal (e.g., an
agile maneuver close to a boundary). A central challenge in this setting is how
to quantify uncertainty in order to choose provably-safe actions that allow us
to collect informative data and reduce uncertainty, thereby achieving both
improved controller safety and optimality. To address this challenge, we
present a deep robust regression model that is trained to directly predict the
uncertainty bounds for safe exploration. We derive generalization bounds for
learning, and connect them with safety and stability bounds in control. We
demonstrate empirically that our robust regression approach can outperform the
conventional Gaussian process (GP) based safe exploration in settings where it
is difficult to specify a good GP prior.

25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
3
The categories of this paper are: physics