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» A Framework for Multiple-Instance Learning
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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
154
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EMNLP
2007
15 years 8 months ago
Structured Prediction Models via the Matrix-Tree Theorem
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...
NAACL
2007
15 years 8 months ago
Source-Language Features and Maximum Correlation Training for Machine Translation Evaluation
We propose three new features for MT evaluation: source-sentence constrained n-gram precision, source-sentence reordering metrics, and discriminative unigram precision, as well as...
Ding Liu, Daniel Gildea
OWLED
2007
15 years 8 months ago
Reasoning with OWL-DL in Inductive Logic Programming
The use of background knowledge and the adoption of Horn clausal logic as a knowledge representation and reasoning framework are the distinguishing features of Inductive Logic Prog...
Francesca A. Lisi
AAAI
2006
15 years 8 months ago
Representing Systems with Hidden State
We discuss the problem of finding a good state representation in stochastic systems with observations. We develop a duality theory that generalizes existing work in predictive sta...
Christopher Hundt, Prakash Panangaden, Joelle Pine...