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
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