Principles and practice of information theory
Principles and practice of information theory
The nature of statistical learning theory
The nature of statistical learning theory
Location- and Density-Based Hierarchical Clustering Using Similarity Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Comparison of approximate methods for handling hyperparameters
Neural Computation
Information Theoretic Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Source Coding Theory
A Similarity-Based Robust Clustering Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
How Many Clusters? An Information-Theoretic Perspective
Neural Computation
Robust support vector machine with bullet hole image classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
Robust least-squares estimation with a relative entropy constraint
IEEE Transactions on Information Theory
A robust deterministic annealing algorithm for data clustering
Data & Knowledge Engineering
Computer Vision and Image Understanding
Improved Adaptive Spatial Information Clustering for Image Segmentation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Adaptive spatial information-theoretic clustering for image segmentation
Pattern Recognition
An information-theoretic fuzzy C-spherical shells clustering algorithm
Fuzzy Sets and Systems
On the weight convergence of Elman networks
IEEE Transactions on Neural Networks
Clustering spherical shells by a mini-max information algorithm
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Robust data clustering in mercer kernel-induced feature space
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
An adaptive spatial information-theoretic fuzzy clustering algorithm for image segmentation
Computer Vision and Image Understanding
An information theoretic sparse kernel algorithm for online learning
Expert Systems with Applications: An International Journal
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We focus on the scenario of robust information clustering (RIC) based on the minimax optimization of mutual information (MI). The minimization of MI leads to the standard mass-constrained deterministic annealing clustering, which is an empirical risk-minimization algorithm. The maximization of MI works out an upper bound of the empirical risk via the identification of outliers (noisy data points). Furthermore, we estimate the real risk VC-bound and determine an optimal cluster number of the RIC based on the structural risk-minimization principle. One of the main advantages of the minimax optimization of MI is that it is a nonparametric approach, which identifies the outliers through the robust density estimate and forms a simple data clustering algorithm based on the square error of the Euclidean distance.