On Convergence of an Iterative Factor Estimate Algorithm for the NFA Model
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Financial APT-Based Gaussian TFA Learning for Adaptive Portfolio Management
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Mining Dependence Structures from Statistical Learning Perspective
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
A Comparative Study on Three MAP Factor Estimate Approaches for NFA
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
BYY harmony learning, structural RPCL, and topological self-organizing on mixture models
Neural Networks - New developments in self-organizing maps
Data smoothing regularization, multi-sets-learning, and problem solving strategies
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Arbitrage pricing theory-based Gaussian temporal factor analysis for adaptive portfolio management
Decision Support Systems - Special issue: Data mining for financial decision making
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
A comparative investigation on subspace dimension determination
Neural Networks - 2004 Special issue: New developments in self-organizing systems
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
Canonical Dual Approach to Binary Factor Analysis
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Optimizing financial portfolios from the perspective of mining temporal structures of stock returns
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
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
Machine learning problems from optimization perspective
Journal of Global Optimization
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First, the relationship between factor analysis (FA) and the well-known arbitrage pricing theory (APT) for financial market is discussed comparatively, with a number of to-be-improved problems listed. An overview is made from a unified perspective on the related studies in the literatures of statistics, control theory, signal processing, and neural networks. Next, we introduce the fundamentals of the Bayesian Ying Yang (BYY) system and the harmony learning principle. We further show that a specific case of the framework, called BYY independent state space (ISS) system, provides a general guide for systematically tackling various FA related learning tasks and the above to-be-improved problems for the APT analyses. Third, on various specific cases of the BYY ISS system in three typical architectures, adaptive algorithms, regularization methods and model selection criteria are provided for either or both of parameter learning with automated model selection and parameter learning followed by model selection. Finally, we introduce some other financial applications that are based on the underlying independent factors via the APT analyses