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Topological Constraints and Kernel-Based Density Estimation
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.ORCID-id: 0000-0003-1114-6040
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.ORCID-id: 0000-0002-5750-9655
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.ORCID-id: 0000-0003-2965-2953
2012 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2012.
Emneord [en]
persistent homology, density estimation, topological constraints
HSV kategori
Forskningsprogram
SRA - Informations- och kommunikationsteknik
Identifikatorer
URN: urn:nbn:se:kth:diva-108161OAI: oai:DiVA.org:kth-108161DiVA, id: diva2:579177
Konferanse
Advances in Neural Information Processing Systems 25, Workshop on Algebraic Topology and Machine Learning, December 8th, Nevada, USA
Forskningsfinansiär
EU, FP7, Seventh Framework Programme, 270436EU, European Research Council, 279933Swedish Foundation for Strategic Research
Merknad

QC 20130115

Tilgjengelig fra: 2012-12-19 Laget: 2012-12-19 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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Pokorny, Florian T.Kjellström, HedvigKragic, Danica

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Totalt: 102 treff
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