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» Learning Gaussian Process Models from Uncertain Data
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ISVC
2009
Springer
14 years 3 months ago
Probabilistic Facial Feature Extraction Using Joint Distribution of Location and Texture Information
Abstract. In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn featu...
Mustafa Berkay Yilmaz, Hakan Erdogan, Mustafa Unel
ICML
2005
IEEE
14 years 9 months ago
Reducing overfitting in process model induction
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
UAI
2008
13 years 10 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 5 months ago
Rules of Thumb for Information Acquisition from Large and Redundant Data
We develop an abstract model of information acquisition from redundant data. We assume a random sampling process from data which contain information with bias and are interested in...
Wolfgang Gatterbauer
ICASSP
2011
IEEE
13 years 6 days ago
Statistical analysis of multi-channel detection using data from airborne AESA radar
We investigate the ground clutter homogeneity and target detection performance using airborne multi-channel AESA (Active Electronically Scanned Array) radar data from flight trial...
Johan Degerman, Thomas Pernstal, Magnus Gisselfalt...