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» Closed Sets for Labeled Data
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COLT
2005
Springer
15 years 10 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
FLAIRS
2007
15 years 7 months ago
Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
Jason Chan, Josiah Poon, Irena Koprinska
AAAI
2006
15 years 6 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
ACL
2004
15 years 6 months ago
Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech
The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding ...
Michelle L. Gregory, Yasemin Altun
ICML
2010
IEEE
15 years 5 months ago
SVM Classifier Estimation from Group Probabilities
A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that ...
Stefan Rüping