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» Robustness of the Learning with Errors Assumption
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DSMML
2004
Springer
15 years 2 months ago
Can Gaussian Process Regression Be Made Robust Against Model Mismatch?
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...
Peter Sollich
LREC
2010
176views Education» more  LREC 2010»
14 years 11 months ago
There's no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known...
Ines Rehbein, Josef Ruppenhofer
ACL
2008
14 years 11 months ago
Analyzing the Errors of Unsupervised Learning
We identify four types of errors that unsupervised induction systems make and study each one in turn. Our contributions include (1) using a meta-model to analyze the incorrect bia...
Percy Liang, Dan Klein
78
Voted
ACL
2009
14 years 7 months ago
Improving Automatic Speech Recognition for Lectures through Transformation-based Rules Learned from Minimal Data
We demonstrate that transformation-based learning can be used to correct noisy speech recognition transcripts in the lecture domain with an average word error rate reduction of 12...
Cosmin Munteanu, Gerald Penn, Xiaodan Zhu
69
Voted
ICPR
2010
IEEE
15 years 4 months ago
Adding Classes Online in Error Correcting Output Codes Framework
—This article proposes a general extension of the Error Correcting Output Codes (ECOC) framework to the online learning scenario. As a result, the final classifier handles the ...
Sergio Escalera, David Masip, Eloi Puertas, Petia ...