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» Prediction on Spike Data Using Kernel Algorithms
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GIS
2007
ACM
15 years 3 months ago
Predicting future locations using clusters' centroids
As technology advances we encounter more available data on moving objects, thus increasing our ability to mine spatiotemporal data. We can use this data for learning moving object...
Sigal Elnekave, Mark Last, Oded Maimon
71
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ICML
2008
IEEE
15 years 10 months ago
An RKHS for multi-view learning and manifold co-regularization
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...
Vikas Sindhwani, David S. Rosenberg
ICML
2001
IEEE
15 years 10 months ago
Estimating a Kernel Fisher Discriminant in the Presence of Label Noise
Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for ...
Bernhard Schölkopf, Neil D. Lawrence
NIPS
2004
14 years 11 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
DSOM
2006
Springer
15 years 1 months ago
Predictable Scaling Behaviour in the Data Centre with Multiple Application Servers
Load sharing in the data centre is an essential strategy for meeting service levels in high volume and high availability services. We investigate the accuracy with which simple, cl...
Mark Burgess, Gard Undheim