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» Semi-supervised Learning from General Unlabeled Data
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ACSW
2004
13 years 9 months ago
Early Assessment of Classification Performance
The ability to distinguish between objects is the fundamental to learning and intelligent behavior in general. The difference between two things is the information we seek; the pr...
Bostjan Brumen, Izidor Golob, Hannu Jaakkola, Tatj...
ALGORITHMICA
2010
95views more  ALGORITHMICA 2010»
13 years 8 months ago
Homogeneous String Segmentation using Trees and Weighted Independent Sets
We divide a string into k segments, each with only one sort of symbols, so as to minimize the total number of exceptions. Motivations come from machine learning and data mining. F...
Peter Damaschke
TNN
2008
114views more  TNN 2008»
13 years 8 months ago
Relevance-Based Feature Extraction for Hyperspectral Images
Abstract--Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific re...
Michael J. Mendenhall, Erzsébet Meré...
JDIM
2010
157views more  JDIM 2010»
13 years 3 months ago
Case studies on context-aware mobile multimedia services
: This paper explores the design, implementation and evaluation of context-aware mobile multimedia services by presenting six case studies on different application domains. The cas...
Timo Ojala
NIPS
1992
13 years 9 months ago
Hidden Markov Model} Induction by Bayesian Model Merging
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
Andreas Stolcke, Stephen M. Omohundro