Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Safe Convex Learning under Uncertain Constraints   We address the problem of minimizing a convex smooth function $f(x)$ over a
compact polyhedral set $D$ given a stochastic zeroth-order constraint feedback
model. This problem arises in safety-critical machine learning applications,
such as personalized medicine and robotics. In such cases, one needs to ensure
constraints are satisfied while exploring the decision space to find optimum of
the loss function. We propose a new variant of the Frank-Wolfe algorithm, which
applies to the case of uncertain linear constraints. Using robust optimization,
we provide the convergence rate of the algorithm while guaranteeing feasibility
of all iterates, with high probability.

12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
1
The categories of this paper are: cs
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ