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» The Use of Classifiers in Sequential Inference
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BMCBI
2008
88views more  BMCBI 2008»
13 years 7 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...
ISLPED
1997
ACM
106views Hardware» more  ISLPED 1997»
13 years 11 months ago
A sequential procedure for average power analysis of sequential circuits
A new statistical technique for average power estimation in sequential circuits is presented. Due to the feedback mechanism, conventional statistical procedures cannot be applied ...
Li-Pen Yuan, Sung-Mo Kang
CORR
2012
Springer
187views Education» more  CORR 2012»
12 years 3 months ago
Sequential Inference for Latent Force Models
Latent force models (LFMs) are hybrid models combining mechanistic principles with non-parametric components. In this article, we shall show how LFMs can be equivalently formulate...
Jouni Hartikainen, Simo Särkkä
FSS
2006
154views more  FSS 2006»
13 years 7 months ago
Sequential Adaptive Fuzzy Inference System (SAFIS) for nonlinear system identification and prediction
In this paper, a Sequential Adaptive Fuzzy Inference System called SAFIS is developed based on the functional equivalence between a radial basis function network and a fuzzy infer...
Hai-Jun Rong, N. Sundararajan, Guang-Bin Huang, P....
JCB
2006
185views more  JCB 2006»
13 years 7 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson