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NIPS
2003
13 years 10 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
DESRIST
2010
Springer
193views Education» more  DESRIST 2010»
14 years 1 months ago
Applying Design Research Artifacts for Building Design Research Artifacts: A Process Model for Enterprise Architecture Planning
Enterprise architecture (EA) describes the fundamental structure of an organization from business to IT. EA as a practice as well as a research topic has been around for several ye...
Stephan Aier, Bettina Gleichauf
ER
2007
Springer
142views Database» more  ER 2007»
14 years 2 months ago
Multidimensional Data Modeling for Business Process Analysis
The emerging area of business process intelligence attempts to enhance the analytical capabilities of business process management systems by employing data warehousing and mining t...
Svetlana Mansmann, Thomas Neumuth, Marc H. Scholl
EDOC
2007
IEEE
14 years 3 months ago
Getting Rid of the OR-Join in Business Process Models
Abstract— In practice, the development of process-aware information systems suffers from a gap between conceptual business process models and executable workflow specifications...
Jan Mendling, Boudewijn F. van Dongen, Wil M. P. v...
ACIIDS
2010
IEEE
204views Database» more  ACIIDS 2010»
14 years 1 months ago
An Unsupervised Learning and Statistical Approach for Vietnamese Word Recognition and Segmentation
There are two main topics in this paper: (i) Vietnamese words are recognized and sentences are segmented into words by using probabilistic models; (ii) the optimum probabilistic mo...
Hieu Le Trung, Vu Le Anh, Kien Le Trung