Fast and robust supervised learning in high dimensions using the geometry of the data

Ujjal Kumar Mukherjee, Subhabrata Majumdar, Snigdhansu Chatterjee

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We develop a method for tracing out the shape of a cloud of sample observations, in arbitrary dimensions, called the data cloud wrapper (DCW). The DCW have strong theoretical properties, have algorithmic scalability and parallel computational features. We further use the DCW to develop a new fast, robust and accurate classification method in high dimensions, called the geometric learning algorithm (GLA). Two of the main features of the proposed algorithm are that there are no assumptions made about the geometric properties of the underlying data generating distribution, and that there are no parametric or other restrictive assumptions made either for the data or the algorithm. The proposed methods are typically faster and more robust than established classification techniques, while being comparably accurate in most cases.

Original languageEnglish (US)
Title of host publicationAdvances in Data Mining
Subtitle of host publicationApplications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings
EditorsPetra Perner
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783319209098
StatePublished - 2015
Event15th Industrial Conference on Data Mining, ICDM 2015 - Hamburg, Germany
Duration: Jul 11 2015Jul 24 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other15th Industrial Conference on Data Mining, ICDM 2015

Bibliographical note

Funding Information:
This research is partially supported by NSF grant # IIS-1029711, NASA grant #-1502546) the Institute on the Environment (IonE), and College of Liberal Arts (CLA) at the University of Minnesota.

Publisher Copyright:
© Springer International Publishing Switzerland 2015.


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