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ICPR
2008
IEEE
16 years 1 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
BIBM
2007
IEEE
159views Bioinformatics» more  BIBM 2007»
16 years 29 days ago
Predicting Future High-Cost Patients: A Real-World Risk Modeling Application
Health care data from patients in the Arizona Health Care Cost Containment System, Arizona’s Medicaid program, provides a unique opportunity to exploit state-of-the-art data pro...
Sai T. Moturu, William G. Johnson, Huan Liu
AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
16 years 24 days ago
Preference Networks: Probabilistic Models for Recommendation Systems
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
ICMCS
2005
IEEE
185views Multimedia» more  ICMCS 2005»
16 years 6 days ago
Automatic Object Trajectory-Based Motion Recognition Using Gaussian Mixture Models
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Gaussian Mixture Models (GMM). We build our models on Principal ...
Faisal I. Bashir, Ashfaq A. Khokhar, Dan Schonfeld
DAGM
2004
Springer
16 years 7 hour ago
Predictive Discretization During Model Selection
We present an approach to discretizing multivariate continuous data while learning the structure of a graphical model. We derive the joint scoring function from the principle of p...
Harald Steck, Tommi Jaakkola