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» Predicting labels for dyadic data
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IJCAI
2003
13 years 11 months ago
Active Learning with Strong and Weak Views: A Case Study on Wrapper Induction
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
Ion Muslea, Steven Minton, Craig A. Knoblock
NAACL
2010
13 years 7 months ago
Extracting Glosses to Disambiguate Word Senses
Like most natural language disambiguation tasks, word sense disambiguation (WSD) requires world knowledge for accurate predictions. Several proxies for this knowledge have been in...
Weisi Duan, Alexander Yates
BMCBI
2011
13 years 1 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
ICDM
2008
IEEE
150views Data Mining» more  ICDM 2008»
14 years 4 months ago
Pseudolikelihood EM for Within-network Relational Learning
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Rongjing Xiang, Jennifer Neville
ECML
2001
Springer
14 years 2 months ago
Classification on Data with Biased Class Distribution
Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
Slobodan Vucetic, Zoran Obradovic