Corrigendum to "BYY learning, regularized implementation, and model selection on modular networks with one hidden layer of binary units" [Neurocomputing 51 (2003) 277-301]
نویسنده
چکیده
Corrigendum Corrigendum to " BYY learning, regularized implementation, and model selection on modular networks with one hidden layer of binary units " The author wishes to make the following corrections: On page 281, the line after Eq. (3): " densities both p(u); q(u) " should be " densities, where both p(u); q(u) are ". On page 285, the ÿrst line of Eq. (20): " y '; t = y ' (x t) " should be " y t; ' = y ' (x t) ". On page 286, the ÿrst line: " (b) comes from (b) " should be " (d) comes from (a) ". On page 287, in the last equation: t; 't should be t; '. On page 288, Step 1 in Table 1: The positions of " BI-architecture " and " B-architecture " should be switched.
منابع مشابه
BYY learning, regularized implementation, and model selection on modular networks with one hidden layer of binary units
The BYY learning has been extended to a modular system, with developments on not only regularized implementation via either normalization or data smoothing, but also the least complexity based model selection. Moreover, both unsupervised and supervised learning have been speci2cally investigated on networks with one hidden layer of binary units. Adaptive EM-like learning algorithms are provided...
متن کاملLearning binary factor analysis with automatic model selection
Binary Factor Analysis (BFA) uncovers the independent binary information sources from observations with wide applications. BFA learning hierarchically nests three levels of inverse problems, i.e., inference of binary code for each observation, parameter estimation and model selection. Under Bayesian YingYang (BYY) framework, the first level becomes an intractable Binary Quadratic Programming (B...
متن کاملA gradient BYY harmony learning rule on Gaussian mixture with automated model selection
One important feature of Bayesian Ying–Yang (BYY) harmony learning is that model selection can be made automatically during parametric learning. In this paper, BYY harmony learning with a bi-directional architecture is studied for Gaussian mixture modelling via a gradient learning rule. It has been demonstrated by simulation experiments that the number of Gaussians can be determined automatical...
متن کاملQuantitative Structure-Activity Relationship Study on Thiosemicarbazone Derivatives as Antitubercular agents Using Artificial Neural Network and Multiple Linear Regression
Background and purpose: Nonlinear analysis methods for quantitative structure–activity relationship (QSAR) studies better describe molecular behaviors, than linear analysis. Artificial neural networks are mathematical models and algorithms which imitate the information process and learning of human brain. Some S-alkyl derivatives of thiosemicarbazone are shown to be beneficial in prevention and...
متن کاملLearning local factor analysis versus mixture of factor analyzers with automatic model selection
Considering Factor Analysis (FA) for each component of Gaussian Mixture Model (GMM), clustering and local dimensionality reduction can be addressed simultaneously by Mixture of Factor Analyzers (MFA) and Local Factor Analysis (LFA), which correspond to two FA parameterizations, respectively. This paper investigates the performance of Variational Bayes (VB) and Bayesian Ying-Yang (BYY) harmony l...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Neurocomputing
دوره 55 شماره
صفحات -
تاریخ انتشار 2003