Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning-Augmented Dynamic Power Management with Multiple States via New
  Ski Rental Bounds   We study the online problem of minimizing power consumption in systems with
multiple power-saving states. During idle periods of unknown lengths, an
algorithm has to choose between power-saving states of different energy
consumption and wake-up costs. We develop a learning-augmented online algorithm
that makes decisions based on (potentially inaccurate) predicted lengths of the
idle periods. The algorithm's performance is near-optimal when predictions are
accurate and degrades gracefully with increasing prediction error, with a
worst-case guarantee almost identical to the optimal classical online algorithm
for the problem. A key ingredient in our approach is a new algorithm for the
online ski rental problem in the learning augmented setting with tight
dependence on the prediction error. We support our theoretical findings with
experiments.

14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph