Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SensibleSleep: A Bayesian Model for Learning Sleep Patterns from
  Smartphone Events   We propose a Bayesian model for extracting sleep patterns from smartphone
events. Our method is able to identify individuals' daily sleep periods and
their evolution over time, and provides an estimation of the probability of
sleep and wake transitions. The model is fitted to more than 400 participants
from two different datasets, and we verify the results against ground truth
from dedicated armband sleep trackers. We show that the model is able to
produce reliable sleep estimates with an accuracy of 0.89, both at the
individual and at the collective level. Moreover the Bayesian model is able to
quantify uncertainty and encode prior knowledge about sleep patterns. Compared
with existing smartphone-based systems, our method requires only screen on/off
events, and is therefore much less intrusive in terms of privacy and more
battery-efficient.

16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph