Competitive learning algorithms for vector quantization
Neural Networks
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
A practical Bayesian framework for backpropagation networks
Neural Computation
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Regularization theory and neural networks architectures
Neural Computation
Training with noise is equivalent to Tikhonov regularization
Neural Computation
The nature of statistical learning theory
The nature of statistical learning theory
Self-organizing maps
Bayesian Ying-Yang machine, clustering and number of clusters
Pattern Recognition Letters - special issue on pattern recognition in practice V
Mixtures of probabilistic principal component analyzers
Neural Computation
On cross validation for model selection
Neural Computation
Mining Dependence Structures from Statistical Learning Perspective
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Temporal BYY learning for state space approach, hidden Markovmodel, and blind source separation
IEEE Transactions on Signal Processing
BYY harmony learning, independent state space, and generalized APT financial analyses
IEEE Transactions on Neural Networks
Mining Dependence Structures from Statistical Learning Perspective
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Data smoothing regularization, multi-sets-learning, and problem solving strategies
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Improved system for object detection and star/galaxy classification via local subspace analysis
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
Genetic-Based EM Algorithm for Learning Gaussian Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparative investigation on subspace dimension determination
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Neural Processing Letters
A nature inspired Ying-Yang approach for intelligent decision support in bank solvency analysis
Expert Systems with Applications: An International Journal
A fast fixed-point BYY harmony learning algorithm on Gaussian mixture with automated model selection
Pattern Recognition Letters
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Investigation on Sparse Kernel Density Estimator Via Harmony Data Smoothing Learning
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
The Competitive EM Algorithm for Gaussian Mixtures with BYY Harmony Criterion
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Automatic Straight Line Detection through Fixed-Point BYY Harmony Learning
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
BYY Harmony Learning on Weibull Mixture with Automated Model Selection
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
A BYY Split-and-Merge EM Algorithm for Gaussian Mixture Learning
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
A Gradient BYY Harmony Learning Algorithm for Straight Line Detection
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
An online Bayesian Ying-Yang learning applied to fuzzy CMAC
Neurocomputing
Online FCMAC-BYY Model with Sliding Window
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Data classification with a generalized Gaussian components based density estimation algorithm
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Bayesian Ying Yang system, best harmony learning, and Gaussian manifold based family
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
Fuzzy CMAC with incremental Bayesian Ying-Yang learning and dynamic rule construction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Matching the dimensionality of maps with that of the data
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Energy based competitive learning
Neurocomputing
Simultaneous model selection and feature selection via BYY harmony learning
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
ACO-based BW algorithm for parameter estimation of hidden Markov models
International Journal of Computer Applications in Technology
A gradient BYY harmony learning algorithm on mixture of experts for curve detection
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
A regularized minimum cross-entropy algorithm on mixtures of experts for time series prediction
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Image segmentation with BYY-RPCL framework
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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The Bayesian Ying-Yang (BYY) harmony learning acts as a general statistical learning framework, featured by not only new regularization techniques for parameter learning but also a new mechanism that implements model selection either automatically during parameter learning or via a new class of model selection criteria used after parameter learning. In this paper, further advances on BYY harmony learning by considering modular inner representations are presented in three parts. One consists of results on unsupervised mixture models, ranging from Gaussian mixture based Mean Square Error (MSE) clustering, elliptic clustering, subspace clustering to NonGaussian mixture based clustering not only with each cluster represented via either Bernoulli-Gaussian mixtures or independent real factor models, but also with independent component analysis implicitly made on each cluster. The second consists of results on supervised mixture-of-experts (ME) models, including Gaussian ME, Radial Basis Function nets, and Kernel regressions. The third consists of two strategies for extending the above structural mixtures into self-organized topological maps. All these advances are introduced with details on three issues, namely, (a) adaptive learning algorithms, especially elliptic, subspace, and structural rival penalized competitive learning algorithms, with model selection made automatically during learning; (b) model selection criteria for being used after parameter learning, and (c) how these learning algorithms and criteria are obtained from typical special cases of BYY harmony learning.