Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Unified Algorithm for Penalized Convolution Smoothed Quantile
  Regression   Penalized quantile regression (QR) is widely used for studying the
relationship between a response variable and a set of predictors under data
heterogeneity in high-dimensional settings. Compared to penalized least
squares, scalable algorithms for fitting penalized QR are lacking due to the
non-differentiable piecewise linear loss function. To overcome the lack of
smoothness, a recently proposed convolution-type smoothed method brings an
interesting tradeoff between statistical accuracy and computational efficiency
for both standard and penalized quantile regressions. In this paper, we propose
a unified algorithm for fitting penalized convolution smoothed quantile
regression with various commonly used convex penalties, accompanied by an
R-language package conquer available from the Comprehensive R Archive Network.
We perform extensive numerical studies to demonstrate the superior performance
of the proposed algorithm over existing methods in both statistical and
computational aspects. We further exemplify the proposed algorithm by fitting a
fused lasso additive QR model on the world happiness data.

15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
1
The categories of this paper are: cs
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg