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COLT
2008
Springer
15 years 6 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
ACL
2008
15 years 6 months ago
Phrase Chunking Using Entropy Guided Transformation Learning
Entropy Guided Transformation Learning (ETL) is a new machine learning strategy that combines the advantages of decision trees (DT) and Transformation Based Learning (TBL). In thi...
Ruy Luiz Milidiú, Cícero Nogueira do...
NIPS
2007
15 years 6 months ago
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations
In transfer learning we aim to solve new problems using fewer examples using information gained from solving related problems. Transfer learning has been successful in practice, a...
M. M. Mahmud, Sylvian R. Ray
APBC
2003
116views Bioinformatics» more  APBC 2003»
15 years 6 months ago
An Empirical Comparison of Supervised Machine Learning Techniques in Bioinformatics
Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely ap...
Aik Choon Tan, David Gilbert
141
Voted
FLAIRS
2003
15 years 6 months ago
LIDS: Learning Intrusion Detection System
The detection of attacks against computer networks is becoming a harder problem to solve in the field of network security. The dexterity of the attackers, the developing technolog...
Mayukh Dass, James Cannady, Walter D. Potter