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Topological Constraints and Kernel-Based Density Estimation
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-1114-6040
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0002-5750-9655
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2965-2953
2012 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This extended abstract1 explores the question of how to estimate a probability distribution from a finite number of samples when information about the topology of the support region of an underlying density is known. This workshop contribution is a continuation of our recent work [1] combining persistent homology and kernel-based density estimation for the first time and in which we explored an approach capable of incorporating topological constraints in bandwidth selection. We report on some recent experiments with high-dimensional motion capture data which show that our method is applicable even in high dimensions and develop our ideas for potential future applications of this framework.

Place, publisher, year, edition, pages
2012.
Keyword [en]
persistent homology, density estimation, topological constraints
National Category
Probability Theory and Statistics Computer Vision and Robotics (Autonomous Systems)
Research subject
SRA - ICT
Identifiers
URN: urn:nbn:se:kth:diva-108161OAI: oai:DiVA.org:kth-108161DiVA: diva2:579177
Conference
Advances in Neural Information Processing Systems 25, Workshop on Algebraic Topology and Machine Learning, December 8th, Nevada, USA
Funder
EU, FP7, Seventh Framework Programme, 270436EU, European Research Council, 279933Swedish Foundation for Strategic Research
Note

QC 20130115

Available from: 2012-12-19 Created: 2012-12-19 Last updated: 2013-02-13Bibliographically approved

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Pokorny, Florian T.Kjellström, HedvigKragic, Danica

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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