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SIGIR
2002
ACM
13 years 7 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 8 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
ICMI
2007
Springer
129views Biometrics» more  ICMI 2007»
14 years 1 months ago
Towards smart meeting: enabling technologies and a real-world application
In this paper, we describe the enabling technologies to develop a smart meeting system based on a three layered generic model. From physical level to semantic level, it consists o...
Zhiwen Yu, Motoyuki Ozeki, Yohsuke Fujii, Yuichi N...
ATAL
2010
Springer
13 years 8 months ago
Learning multirobot joint action plans from simultaneous task execution demonstrations
The central problem of designing intelligent robot systems which learn by demonstrations of desired behaviour has been largely studied within the field of robotics. Numerous archi...
Murilo Fernandes Martins, Yiannis Demiris
COMPGEOM
2011
ACM
12 years 11 months ago
Metric graph reconstruction from noisy data
Many real-world data sets can be viewed of as noisy samples of special types of metric spaces called metric graphs [16]. Building on the notions of correspondence and GromovHausdo...
Mridul Aanjaneya, Frédéric Chazal, D...