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NIPS
2003
13 years 10 months ago
Error Bounds for Transductive Learning via Compression and Clustering
This paper is concerned with transductive learning. Although transduction appears to be an easier task than induction, there have not been many provably useful algorithms and boun...
Philip Derbeko, Ran El-Yaniv, Ron Meir
CBMS
2009
IEEE
14 years 3 months ago
Lessons learned in developing a low-cost high performance medical imaging cluster
This paper explores the usefulness of the Sony PlayStation 3 R (PS3) for medical image processing. Medical image processing often entails dealing with a large number of high resol...
Kirt D. Lillywhite, Dah-Jye Lee, Sameer Antani, Do...
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
ECAI
2000
Springer
14 years 1 months ago
Designing Clustering Methods for Ontology Building - The Mo'K Workbench
This paper describes Mo’K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo’K is intended to assist ontology de...
Gilles Bisson, Claire Nedellec, Dolores Cañ...
ICML
2004
IEEE
14 years 9 months ago
Multi-task feature and kernel selection for SVMs
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Tony Jebara