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» Gaussian processes and limiting linear models
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EOR
2007
165views more  EOR 2007»
13 years 11 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
ISBI
2006
IEEE
14 years 11 months ago
Linearly constrained MEG beamformers for MVAR modeling of cortical interactions
Among the many methods for modeling cortical interactions using EEG and MEG data, Multivariate Autoregressive(MVAR) functional connectivity measures have the advantage of providin...
Hua Brian Hui, Richard M. Leahy
TSP
2011
151views more  TSP 2011»
13 years 5 months ago
Stochastic Models for Sparse and Piecewise-Smooth Signals
Abstract—We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential...
Michael Unser, Pouya Dehghani Tafti
HPCA
2006
IEEE
14 years 11 months ago
Construction and use of linear regression models for processor performance analysis
Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in ma...
P. J. Joseph, Kapil Vaswani, Matthew J. Thazhuthav...
DAC
2000
ACM
14 years 3 months ago
An asymptotically constant, linearly bounded methodology for the statistical simulation of analog circuits including component m
Abstract: This paper presents a new statistical methodology to simulate the effect of both inter-die and intra-die variation on the electrical performance of analog integrated circ...
Carlo Guardiani, Sharad Saxena, Patrick McNamara, ...