Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: RobustTrend: A Huber Loss with a Combined First and Second Order
  Difference Regularization for Time Series Trend Filtering   Extracting the underlying trend signal is a crucial step to facilitate time
series analysis like forecasting and anomaly detection. Besides noise signal,
time series can contain not only outliers but also abrupt trend changes in
real-world scenarios. To deal with these challenges, we propose a robust trend
filtering algorithm based on robust statistics and sparse learning.
Specifically, we adopt the Huber loss to suppress outliers, and utilize a
combination of the first order and second order difference on the trend
component as regularization to capture both slow and abrupt trend changes.
Furthermore, an efficient method is designed to solve the proposed robust trend
filtering based on majorization minimization (MM) and alternative direction
method of multipliers (ADMM). We compared our proposed robust trend filter with
other nine state-of-the-art trend filtering algorithms on both synthetic and
real-world datasets. The experiments demonstrate that our algorithm outperforms
existing methods.

20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
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The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio