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» Experimental perspectives on learning from imbalanced data
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KCAP
2009
ACM
14 years 2 months ago
Reducing class imbalance during active learning for named entity annotation
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...
Katrin Tomanek, Udo Hahn
IJCV
2010
169views more  IJCV 2010»
13 years 6 months ago
Rigid Structure from Motion from a Blind Source Separation Perspective
We present an information theoretic approach to define the problem of structure from motion (SfM) as a blind source separation one. Given that for almost all practical joint densi...
Jeff Fortuna, Aleix M. Martínez
SIGIR
2012
ACM
11 years 10 months ago
Inferring missing relevance judgments from crowd workers via probabilistic matrix factorization
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
Hyun Joon Jung, Matthew Lease
NCA
2006
IEEE
13 years 7 months ago
Analysing the localisation sites of proteins through neural networks ensembles
Scientists involved in the area of proteomics are currently seeking integrated, customised and validated research solutions to better expedite their work in proteomics analyses and...
Aristoklis D. Anastasiadis, George D. Magoulas
COOPIS
2004
IEEE
13 years 11 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar