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Alex Gammerman - PhD Students Supervised

PhD Awarded:

David Lindsay
Forecasting Models
2006

Tony Belotti
Feature Selection and Pattern Recognition Problems with Microarrays
2006

Thomas Melluish
Regression by transduction and its application to medical diagnosis
2005

Daniil Ryabko
'Lazy' Learning Algorithms
2005

Leo Gordon
Application of Support Vector Machine with Sequence Alignment and other kernels in genomic signal recognition
2004

Harris Papadopoulos
Qualified Predictions for Large Data Sets
2004

Konstantinos Proedrou
Rigourous Measures of Confidence for Pattern Recognition and Regression
2004

David Surkov
Inductive Confidence Machine for Pattern Recognition: is it the next step towards AI?
2004

Ilia Nouretdinov
Algorithmic theory of randomness and its applications
2003

Craig Saunders
Transductive inference and its application to pattern recognition
2000

Mark Stitson
Design, Implentation and Applications of the Support Vector Method Learning Algorithm
1999

Jason Weston
Destiny estimation problem
1999

Yiqun Gu
A Bayesian System For Computer-Aided Diagnosis Without Assuming Conditional Independence
1992

Thomas Kane
Reasoning with Uncertainty using Nilsson's Probabilistic Logic and the Maximum Entropy Formulism
1992

Zhiyuan Luo
A Probabilistic Reasoning and Learning System Based on Bayesian Belief Networks
1992

Xiaohui Liu
Probability-related Treatment of Uncertainty in Knowledge-based Systems.
1988

 

Current PhD Students:

Brian Burford
Defensive Forecasting

David Lindsay
Reliability and Cailibration in Probabilistic Forecasts

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Last updated 18/12/07 9:41 / AGB