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135
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NIPS
2008
15 years 4 months 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
113
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BMCBI
2007
126views more  BMCBI 2007»
15 years 2 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
152
Voted
EOR
2007
165views more  EOR 2007»
15 years 2 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
BMCBI
2005
121views more  BMCBI 2005»
15 years 2 months ago
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) ma
Background: Proteomic profiling of complex biological mixtures by the ProteinChip technology of surfaceenhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectro...
Huixiao Hong, Yvonne P. Dragan, Joshua Epstein, Ca...
143
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NN
2002
Springer
208views Neural Networks» more  NN 2002»
15 years 2 months ago
A spiking neuron model: applications and learning
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...