GTM: the generative topographic mapping
Neural Computation
Learning and Design of Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
A k-segments algorithm for finding principal curves
Pattern Recognition Letters
A robust algorithm for image principal curve detection
Pattern Recognition Letters
Wavelet thresholding via MDL for natural images
IEEE Transactions on Information Theory
Spatially adaptive wavelet denoising using the minimum description length principle
IEEE Transactions on Image Processing
Extraction of curvilinear features from noisy point patterns using principal curves
Pattern Recognition Letters
Regularization-free principal curve estimation
The Journal of Machine Learning Research
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This paper studies the k-segments algorithm proposed by Verbeek et al. [Verbeek, J.J., Vlassis, N., Krose, B., 2002. A k-segments algorithm for finding principal curves, Pattern Recognition Lett. 23, 1009-1017] for computing principal curves. In particular an automatic method for choosing the ''free'' parameters in this k-segments algorithm is proposed. Experimental results are provided to demonstrate the performance of this proposed method.