Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Group Fairness in Bandit Arm Selection   We propose a novel formulation of group fairness with biased feedback in the
contextual multi-armed bandit (CMAB) setting. In the CMAB setting, a sequential
decision maker must, at each time step, choose an arm to pull from a finite set
of arms after observing some context for each of the potential arm pulls. In
our model, arms are partitioned into two or more sensitive groups based on some
protected feature(s) (e.g., age, race, or socio-economic status). Initial
rewards received from pulling an arm may be distorted due to some unknown
societal or measurement bias. We assume that in reality these groups are equal
despite the biased feedback received by the agent. To alleviate this, we learn
a societal bias term which can be used to both find the source of bias and to
potentially fix the problem outside of the algorithm. We provide a novel
algorithm that can accommodate this notion of fairness for an arbitrary number
of groups, and provide a theoretical bound on the regret for our algorithm. We
validate our algorithm using synthetic data and two real-world datasets for
intervention settings wherein we want to allocate resources fairly across
groups.

37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat