Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Bandit Linear Optimization: A Study   This article introduces the concepts around Online Bandit Linear Optimization
and explores an efficient setup called SCRiBLe (Self-Concordant Regularization
in Bandit Learning) created by Abernethy et. al.\cite{abernethy}. The SCRiBLe
setup and algorithm yield a $O(\sqrt{T})$ regret bound and polynomial run time
complexity bound on the dimension of the input space. In this article we build
up to the bandit linear optimization case and study SCRiBLe.

25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
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The categories of this paper are: bayes-an
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph