Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contextual Bandits with Continuous Actions: Smoothing, Zooming, and
  Adapting   We study contextual bandit learning with an abstract policy class and
continuous action space. We obtain two qualitatively different regret bounds:
one competes with a smoothed version of the policy class under no continuity
assumptions, while the other requires standard Lipschitz assumptions. Both
bounds exhibit data-dependent "zooming" behavior and, with no tuning, yield
improved guarantees for benign problems. We also study adapting to unknown
smoothness parameters, establishing a price-of-adaptivity and deriving optimal
adaptive algorithms that require no additional information.

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The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
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The categories of this paper are: q-fin
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat