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NIPS
2001
13 years 9 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
ICAS
2006
IEEE
139views Robotics» more  ICAS 2006»
14 years 1 months ago
Predicting Resource Demand in Dynamic Utility Computing Environments
— We target the problem of predicting resource usage in situations where the modeling data is scarce, non-stationary, or expensive to obtain. This scenario occurs frequently in c...
Artur Andrzejak, Sven Graupner, Stefan Plantikow
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
13 years 11 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
AAAI
2008
13 years 10 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
BMCBI
2010
115views more  BMCBI 2010»
13 years 7 months ago
Assessment and optimisation of normalisation methods for dual-colour antibody microarrays
Background: Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour a...
Martin Sill, Christoph Schroder, Jörg D. Hohe...