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ECML
2006
Springer
15 years 1 months ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...
APBC
2003
128views Bioinformatics» more  APBC 2003»
14 years 11 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
BMCBI
2010
159views more  BMCBI 2010»
14 years 9 months ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao
FGR
2000
IEEE
159views Biometrics» more  FGR 2000»
15 years 2 months ago
Gesture Modeling and Recognition Using Finite State Machines
This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...
Pengyu Hong, Thomas S. Huang, Matthew Turk
ICML
2010
IEEE
14 years 10 months ago
Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
Nicholas Bartlett, David Pfau, Frank Wood