Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An LS-Decomposition Approach for Robust Data Recovery in Wireless Sensor
  Networks   Wireless sensor networks are widely adopted in military, civilian and
commercial applications, which fuels an exponential explosion of sensory data.
However, a major challenge to deploy effective sensing systems is the presence
of {\em massive missing entries, measurement noise, and anomaly readings}.
Existing works assume that sensory data matrices have low-rank structures. This
does not hold in reality due to anomaly readings, causing serious performance
degradation. In this paper, we introduce an {\em LS-Decomposition} approach for
robust sensory data recovery, which decomposes a corrupted data matrix as the
superposition of a low-rank matrix and a sparse anomaly matrix. First, we prove
that LS-Decomposition solves a convex program with bounded approximation error.
Second, using data sets from the IntelLab, GreenOrbs, and NBDC-CTD projects, we
find that sensory data matrices contain anomaly readings. Third, we propose an
accelerated proximal gradient algorithm and prove that it approximates the
optimal solution with convergence rate $O(1/k^2)$ ($k$ is the number of
iterations). Evaluations on real data sets show that our scheme achieves
recovery error $\leq 5\%$ for sampling rate $\geq 50\%$ and almost exact
recovery for sampling rate $\geq 60\%$, while state-of-the-art methods have
error $10\% \sim 15\%$ at sampling rate $90\%$.

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The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
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The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
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The categories of this paper are: eess
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The categories of this paper are: dg-ga
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The categories of this paper are: funct-an
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The categories of this paper are: quant-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-th
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The categories of this paper are: q-fin
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The categories of this paper are: comp-gas
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The categories of this paper are: econ
8
The categories of this paper are: hep-ex