Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A One-Size-Fits-All Solution to Conservative Bandit Problems   In this paper, we study a family of conservative bandit problems (CBPs) with
sample-path reward constraints, i.e., the learner's reward performance must be
at least as well as a given baseline at any time. We propose a
One-Size-Fits-All solution to CBPs and present its applications to three
encompassed problems, i.e. conservative multi-armed bandits (CMAB),
conservative linear bandits (CLB) and conservative contextual combinatorial
bandits (CCCB). Different from previous works which consider high probability
constraints on the expected reward, we focus on a sample-path constraint on the
actually received reward, and achieve better theoretical guarantees
($T$-independent additive regrets instead of $T$-dependent) and empirical
performance. Furthermore, we extend the results and consider a novel
conservative mean-variance bandit problem (MV-CBP), which measures the learning
performance with both the expected reward and variability. For this extended
problem, we provide a novel algorithm with $O(1/T)$ normalized additive regrets
($T$-independent in the cumulative form) and validate this result through
empirical evaluation.

35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga