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» Sampling Methods for Unsupervised Learning
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CORR
2010
Springer
150views Education» more  CORR 2010»
15 years 2 months ago
Don't 'have a clue'? Unsupervised co-learning of downward-entailing operators
Researchers in textual entailment have begun to consider inferences involving downward-entailing operators, an interesting and important class of lexical items that change the way...
Cristian Danescu-Niculescu-Mizil, Lillian Lee
111
Voted
CSB
2004
IEEE
106views Bioinformatics» more  CSB 2004»
15 years 6 months ago
Positive Sample Only Learning (PSOL) for Predicting RNA Genes in E. coli
RNA genes lack most of the signals used for protein gene identification. A major shortcoming of previous discriminative methods to distinguish functional RNA (fRNA) genes from oth...
Richard F. Meraz, Xiaofeng He, Chris H. Q. Ding, S...
ACL
2009
15 years 3 days ago
Recognizing Stances in Online Debates
This paper presents an unsupervised opinion analysis method for debate-side classification, i.e., recognizing which stance a person is taking in an online debate. In order to hand...
Swapna Somasundaran, Janyce Wiebe
BMCBI
2008
99views more  BMCBI 2008»
15 years 2 months ago
Binning sequences using very sparse labels within a metagenome
Background: In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the cu...
Chon-Kit Kenneth Chan, Arthur L. Hsu, Saman K. Hal...
IJCNN
2008
IEEE
15 years 8 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...