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» Semi-supervised Learning from General Unlabeled Data
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ML
2008
ACM
150views Machine Learning» more  ML 2008»
13 years 7 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
KDD
2007
ACM
189views Data Mining» more  KDD 2007»
14 years 8 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
ECAI
2004
Springer
14 years 1 months ago
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
CVPR
2009
IEEE
15 years 3 months ago
Learning from Ambiguously Labeled Images
In many image and video collections, we have access only to partially labeled data. For example, personal photo collections often contain several faces per image and a caption t...
Benjamin Sapp, Benjamin Taskar, Chris Jordan, Timo...
IDEAL
2007
Springer
14 years 2 months ago
Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles
The dependence of the classification error on the size of a bagging ensemble can be modeled within the framework of Monte Carlo theory for ensemble learning. These error curves ar...
Daniel Hernández-Lobato, Gonzalo Mart&iacut...