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COLT
1998
Springer
13 years 11 months ago
Learning One-Variable Pattern Languages in Linear Average Time
A new algorithm for learning one-variable pattern languages is proposed and analyzed with respect to its average-case behavior. We consider the total learning time that takes into...
Rüdiger Reischuk, Thomas Zeugmann
MLDM
2007
Springer
14 years 1 months ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 3 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
AAAI
2008
13 years 10 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
MICCAI
2008
Springer
14 years 8 months ago
AutoGate: Fast and Automatic Doppler Gate Localization in B-Mode Echocardiogram
In this paper, we propose a so-called AutoGate algorithm for fast and automatic Doppler gate localization in B-mode echocardiography. The algorithm has two components: 1) cardiac s...
Jin Hyeong Park, Shaohua Kevin Zhou, Costas Simo...