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» Generalizing over Several Learning Settings
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CIKM
2006
Springer
13 years 11 months ago
Evaluation by comparing result sets in context
Familiar evaluation methodologies for information retrieval (IR) are not well suited to the task of comparing systems in many real settings. These systems and evaluation methods m...
Paul Thomas, David Hawking
ECML
2004
Springer
14 years 1 months ago
A Boosting Approach to Multiple Instance Learning
In this paper we present a boosting approach to multiple instance learning. As weak hypotheses we use balls (with respect to various metrics) centered at instances of positive bags...
Peter Auer, Ronald Ortner
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
ICML
2007
IEEE
14 years 8 months ago
Multiclass multiple kernel learning
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Alexander Zien, Cheng Soon Ong
CIKM
2010
Springer
13 years 6 months ago
Rank learning for factoid question answering with linguistic and semantic constraints
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...