Machine Learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Learning Mixtures of Gaussians
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
An Algorithmic Theory of Learning: Robust Concepts and Random Projection
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
International Journal of Information and Communication Technology
Sorted random projections for robust rotation-invariant texture classification
Pattern Recognition
A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces
Pattern Recognition Letters
A set correlation model for partitional clustering
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Random projection, margins, kernels, and feature-selection
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Iterative random projections for high-dimensional data clustering
Pattern Recognition Letters
Distributed high dimensional information theoretical image registration via random projections
Digital Signal Processing
Random direction divisive clustering
Pattern Recognition Letters
Improving classification accuracy on uncertain data by considering multiple subclasses
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Tensor clustering via adaptive subspace iteration
Intelligent Data Analysis
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Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gaussians. Here we summarize these results and illustrate them by a wide variety of experiments on synthetic and real data.