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ICPR
2008
IEEE
15 years 6 months ago
Manifold denoising with Gaussian Process Latent Variable Models
For a finite set of points lying on a lower dimensional manifold embedded in a high-dimensional data space, algorithms have been developed to study the manifold structure. Howeve...
Yan Gao, Kap Luk Chan, Wei-Yun Yau
SAC
2006
ACM
15 years 5 months ago
An evaluation of conceptual business process modelling languages
Conceptual Business Process Modelling Languages (BPMLs) express certain aspects of processes (e.g. activities, roles, interactions, data, etc.) and address different application a...
Beate List, Birgit Korherr
MCS
2005
Springer
15 years 5 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
NIPS
2003
15 years 1 months ago
Learning Non-Rigid 3D Shape from 2D Motion
This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
ESSMAC
2003
Springer
15 years 4 months ago
Filtered Gaussian Processes for Learning with Large Data-Sets
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...