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» Gaussian processes and limiting linear models
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TC
2010
13 years 5 months ago
Model-Driven System Capacity Planning under Workload Burstiness
In this paper, we define and study a new class of capacity planning models called MAP queueing networks. MAP queueing networks provide the first analytical methodology to describe ...
Giuliano Casale, Ningfang Mi, Evgenia Smirni
BMCBI
2006
115views more  BMCBI 2006»
13 years 11 months ago
Multivariate curve resolution of time course microarray data
Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
ICIP
2005
IEEE
15 years 18 days ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
TIT
2002
65views more  TIT 2002»
13 years 10 months ago
On the importance of combining wavelet-based nonlinear approximation with coding strategies
This paper provides a mathematical analysis of transform compression in its relationship to linear and nonlinear approximation theory. Contrasting linear and nonlinear approximatio...
Albert Cohen, Ingrid Daubechies, Onur G. Guleryuz,...
NIPS
2008
14 years 11 days ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink