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COLT
2008
Springer
13 years 11 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
AAAI
2010
13 years 10 months ago
Multi-Task Active Learning with Output Constraints
Many problems in information extraction, text mining, natural language processing and other fields exhibit the same property: multiple prediction tasks are related in the sense th...
Yi Zhang 0010
SIAMDM
2008
105views more  SIAMDM 2008»
13 years 9 months ago
Average Spectra and Minimum Distances of Low-Density Parity-Check Codes over Abelian Groups
Ensembles of regular low-density parity-check codes over any finite Abelian group G are studied. The nonzero entries of the parity matrix are randomly chosen, independently and uni...
Giacomo Como, Fabio Fagnani
SIAMDM
2002
124views more  SIAMDM 2002»
13 years 9 months ago
Counting Claw-Free Cubic Graphs
Let Hn be the number of claw-free cubic graphs on 2n labeled nodes. Combinatorial reductions are used to derive a second order, linear homogeneous differential equation with polyno...
Edgar M. Palmer, Ronald C. Read, Robert W. Robinso...
TMI
2002
185views more  TMI 2002»
13 years 9 months ago
A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data
In this paper, we present a novel algorithm for fuzzy segmentation of magnetic resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI inten...
Mohamed N. Ahmed, Sameh M. Yamany, Nevin Mohamed, ...