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» Why Is Rule Learning Optimistic and How to Correct It
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ECML
2006
Springer
14 years 3 days ago
Why Is Rule Learning Optimistic and How to Correct It
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
CSIE
2009
IEEE
14 years 3 months ago
Automatic Preposition Errors Correction Using Inductive Learning
In this paper, we describe a system for correcting English preposition errors automatically. Non-native English writers often make these errors. Our system uses rules extracted au...
Hokuto Ototake, Kenji Araki
BMCBI
2010
140views more  BMCBI 2010»
13 years 5 months ago
An improved machine learning protocol for the identification of correct Sequest search results
Background: Mass spectrometry has become a standard method by which the proteomic profile of cell or tissue samples is characterized. To fully take advantage of tandem mass spectr...
Morten Kallberg, Hui Lu
EACL
2003
ACL Anthology
13 years 9 months ago
Learning to Identify Fragmented Words in Spoken Discourse
Disfluent speech adds to the difficulty of processing spoken language utterances. In this paper we concentrate on identifying one disfluency phenomenon: fragmented words. Our d...
Piroska Lendvai
ICML
2010
IEEE
13 years 9 months ago
Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences
This paper studies the problem of learning from ambiguous supervision, focusing on the task of learning semantic correspondences. A learning problem is said to be ambiguously supe...
Antoine Bordes, Nicolas Usunier, Jason Weston