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JMLR
2006
389views more  JMLR 2006»
13 years 7 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
ICANN
2011
Springer
12 years 11 months ago
Learning Curves for Gaussian Processes via Numerical Cubature Integration
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...
Simo Särkkä
IJCNN
2006
IEEE
14 years 1 months ago
Rao-Blackwellized Particle Filtering for Sequential Speech Enhancement
— In this paper we present a method of sequential speech enhancement, where we infer clean speech signal using a Rao-Blackwellized particle filter (RBPF), given a noisecontamina...
Sunho Park, Seungjin Choi
IFIP12
2008
13 years 9 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...
IJNS
2010
106views more  IJNS 2010»
13 years 6 months ago
Cascade Process Modeling with Mechanism-Based Hierarchical Neural Networks
Abstract: Cascade process, such as wastewater treatment plant, includes many nonlinear subsystems and many variables. When the number of sub-systems is big, the input-output relati...
Qiumei Cong, Wen Yu, Tianyou Chai