Penalized Quantile Regression for Distributed Big Data Using the Slack Variable Representation

Author(s):  
Ye Fan ◽  
Nan Lin ◽  
Xianjun Yin
2020 ◽  
Vol 18 (06) ◽  
pp. 1057-1075
Author(s):  
Lei Wang ◽  
Heng Lian

Distributed estimation has received increasing attention in the last several years and is particularly useful in the big data setting. Both mean regression and quantile regression has been investigated recently. In this paper, we consider distributed quantile regression with high dimension using a lasso penalty for sparse modeling. We extend a previous communication-efficient approach resulting in a method for distributed quantile regression without the need to smooth the loss or the gradient of the loss. The method is simple to implement and we present some numerical studies with encouraging performances.


2017 ◽  
Vol 85 (3) ◽  
pp. 494-518 ◽  
Author(s):  
Liqun Yu ◽  
Nan Lin
Keyword(s):  
Big Data ◽  

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org


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