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» A Kernel Between Sets of Vectors
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BMCBI
2006
148views more  BMCBI 2006»
13 years 8 months ago
Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores
Background: Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epi...
Jesper Salomon, Darren R. Flower
ICPR
2008
IEEE
14 years 10 months ago
Fast protein homology and fold detection with sparse spatial sample kernels
In this work we present a new string similarity feature, the sparse spatial sample (SSS). An SSS is a set of short substrings at specific spatial displacements contained in the or...
Pai-Hsi Huang, Pavel P. Kuksa, Vladimir Pavlovic
JC
2008
128views more  JC 2008»
13 years 8 months ago
Lattice rule algorithms for multivariate approximation in the average case setting
We study multivariate approximation for continuous functions in the average case setting. The space of d variate continuous functions is equipped with the zero mean Gaussian measu...
Frances Y. Kuo, Ian H. Sloan, Henryk Wozniakowski
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 9 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
NIPS
2001
13 years 10 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio