High dimensional analysis of time series data and Machine learning problems

Last updated 3rd Jul 2017
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A pinboard by Brandon Park

Ph.D Candidate, George Mason University

PINBOARD SUMMARY

Network based methodologies for time series that provide new insights into causality and forecasting

High dimensional time series is concerned with data that are characterized by small sample sizes and a large number of features with time trends. As an example, while forecasting the national GDP ...

6 ITEMS PINNED

#1
Should we sample a time series more frequently?: decision support via multirate spectrum estimation
Research published 18th Dec 2016 in Journal of ...
Pinned 3rd Jul 2017
#2
Predictive learning machine-based approach to detect traffic outside of service level agreements
Free access available
Patent published 10th May 2016 by the USPTO
Pinned 3rd Jul 2017
#3
An Interactive Machine Learning Framework
Research published 18th Oct 2016 in arXiv - Com...
Pinned 3rd Jul 2017
#4
The time dependency predictive model on the basis of community detection and long-short term memory
Research published 20th Jun 2017 in Concurrency...
Pinned 30th Jun 2017
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