Local convergence analysis of a grouped variable version of coordinate descent
Journal of Optimization Theory and Applications
Convergence theory for fuzzy c-means: counterexamples and repairs
IEEE Transactions on Systems, Man and Cybernetics
Journal of Optimization Theory and Applications
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Optimization by Vector Space Methods
Optimization by Vector Space Methods
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Local convergence of tri-level alternating optimization
Neural, Parallel & Scientific Computations
Mathematical Methods for Neural Network Analysis and Design
Mathematical Methods for Neural Network Analysis and Design
Fuzzy Systems: Modeling and Control
Fuzzy Systems: Modeling and Control
Fuzzy c-means clustering of incomplete data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches
Neural Processing Letters
Convergence of alternating optimization
Neural, Parallel & Scientific Computations
Learning spatially variant dissimilarity (SVaD) measures
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning spatially variant dissimilarity (SVaD) measures
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A fast iterative algorithm for fisher discriminant using heterogeneous kernels
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A two-stage approach to domain adaptation for statistical classifiers
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Feedback reduction in uplink MIMO OFDM systems by chunk optimization
EURASIP Journal on Advances in Signal Processing
An Improved Multi-task Learning Approach with Applications in Medical Diagnosis
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Learning sparse kernels from 3D surfaces for heart wall motion abnormality detection
IAAI'08 Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3
Automatic taxonomy generation: issues and possibilities
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Double sparsity: learning sparse dictionaries for sparse signal approximation
IEEE Transactions on Signal Processing
Feature fusion using locally linear embedding for classification
IEEE Transactions on Neural Networks
Robust Tomlinson-Harashima Precoders for Multiuser MISO Downlink with Imperfect CSI
Wireless Personal Communications: An International Journal
Plant species recognition based on radial basis probabilistic neural networks ensemble classifier
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Decentralized limited-feedback multiuser MIMO for temporally correlated channels
Journal of Electrical and Computer Engineering
The Key to Three-View Geometry
International Journal of Computer Vision
Simultaneous similarity learning and feature-weight learning for document clustering
TextGraphs-6 Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing
Image classification by multimodal subspace learning
Pattern Recognition Letters
LinkFCM: Relation integrated fuzzy c-means
Pattern Recognition
Learning neighborhoods for metric learning
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Learning classification models from multiple experts
Journal of Biomedical Informatics
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Let f : Rs 驴 R be a real-valued scalar field, and let x = (x1,..., xs)T 驴 Rs be partitioned into t subsets of non-overlapping variables as x = (X1,...,Xt)T, with Xi 驴 Rpi, for i = 1, ..., t, 驴i=1tPi = s. Alternating optimization (AO) is an iterative procedure for minimizing (or maximizing) the function f(x) = f(X1,X2,...,Xt) jointly over all variables by alternating restricted minimizations over the individual subsets of variables X1,...,Xt. AO is the basis for the c-means clustering algorithms (t=2), many forms of vector quantization (t = 2, 3 and 4), and the expectation-maximization (EM) algorithm (t = 4) for normal mixture decomposition. First we review where and how AO fits into the overall optimization landscape. Then we discuss the important theoretical issues connected with the AO approach. Finally, we state (without proofs) two new theorems that give very general local and global convergence and rate of convergence results which hold for all partitionings of x.