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» A supervised learning approach for imbalanced data sets
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DAGM
2008
Springer
15 years 8 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof
KDD
2007
ACM
189views Data Mining» more  KDD 2007»
16 years 6 months ago
Corroborate and learn facts from the web
The web contains lots of interesting factual information about entities, such as celebrities, movies or products. This paper describes a robust bootstrapping approach to corrobora...
Shubin Zhao, Jonathan Betz
JMLR
2010
101views more  JMLR 2010»
15 years 1 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
ICDM
2006
IEEE
164views Data Mining» more  ICDM 2006»
16 years 16 days ago
Unsupervised Learning of Tree Alignment Models for Information Extraction
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
Philip Zigoris, Damian Eads, Yi Zhang
ICDM
2003
IEEE
136views Data Mining» more  ICDM 2003»
15 years 11 months ago
Statistical Relational Learning for Document Mining
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence...