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» On Clusterings - Good, Bad and Spectral
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PRL
2008
135views more  PRL 2008»
13 years 8 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Discrete Regularization for Perceptual Image Segmentation via Semi-Supervised Learning and Optimal Control
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Hongwei Zheng, Olaf Hellwich
SPIESR
2003
136views Database» more  SPIESR 2003»
13 years 9 months ago
Media segmentation using self-similarity decomposition
We present a framework for analyzing the structure of digital media streams. Though our methods work for video, text, and audio, we concentrate on detecting the structure of digit...
Jonathan Foote, Matthew L. Cooper
PR
2008
123views more  PR 2008»
13 years 8 months ago
Extensions of vector quantization for incremental clustering
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Edwin Lughofer
ICASSP
2009
IEEE
14 years 3 months ago
On the phonetic information in ultrasonic microphone signals
We study the phonetic information in the signal from an ultrasonic “microphone”, a device that emits an ultrasonic wave toward a speaker and receives the reflected, Doppler-s...
Karen Livescu, Bo Zhu, James R. Glass