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» Parametric Process Model Inference
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CODES
2006
IEEE
14 years 1 months ago
Yield prediction for architecture exploration in nanometer technology nodes: : a model and case study for memory organizations
Process variability has a detrimental impact on the performance of memories and other system components, which can lead to parametric yield loss at the system level due to timing ...
Antonis Papanikolaou, T. Grabner, Miguel Miranda, ...
PROMISE
2010
13 years 2 months ago
Case-based reasoning vs parametric models for software quality optimization
Background: There are many data mining methods but few comparisons between them. For example, there are at least two ways to build quality optimizers, programs that find project o...
Adam Brady, Tim Menzies
NIPS
2008
13 years 9 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
ICASSP
2007
IEEE
14 years 1 months ago
A Parametric Method for Pitch Estimation of Piano Tones
The efficiency of most pitch estimation methods declines when the analyzed frame is shortened and/or when a wide fundamental frequency (F0) range is targeted. The technique propo...
Valentin Emiya, Bertrand David, Roland Badeau
ICASSP
2011
IEEE
12 years 11 months ago
Approximation of pattern transformation manifolds with parametric dictionaries
The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...
Elif Vural, Pascal Frossard