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ECML
2003
Springer
13 years 9 months ago
Ensembles of Multi-instance Learners
In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. Through analyzin...
Zhi-Hua Zhou, Min-Ling Zhang
ECML
2003
Springer
13 years 9 months ago
A Two-Level Learning Method for Generalized Multi-instance Problems
In traditional multi-instance (MI) learning, a single positive instance in a bag produces a positive class label. Hence, the learner knows how the bag’s class label depends on th...
Nils Weidmann, Eibe Frank, Bernhard Pfahringer
ECML
2003
Springer
13 years 9 months ago
Offspring-annotated probabilistic context-free grammars
Jose L. Verdú-Mas, Jorge Calera-Rubio, Rafa...
ECML
2003
Springer
13 years 9 months ago
Optimizing Local Probability Models for Statistical Parsing
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems ...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
ECML
2003
Springer
13 years 9 months ago
A Generative Model for Semantic Role Labeling
Determining the semantic role of sentence constituents is a key task in determining sentence meanings lying behind a veneer of variant syntactic expression. We present a model of n...
Cynthia A. Thompson, Roger Levy, Christopher D. Ma...
ECML
2003
Springer
13 years 9 months ago
Learning Context Free Grammars in the Limit Aided by the Sample Distribution
We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...
Yoav Seginer
ECML
2003
Springer
13 years 9 months ago
Experiments with Cost-Sensitive Feature Evaluation
Many machine learning tasks contain feature evaluation as one of its important components. This work is concerned with attribute estimation in the problems where class distribution...
Marko Robnik-Sikonja
ECML
2003
Springer
13 years 9 months ago
Leveraging Lexical Semantics to Infer Context-Free Grammars
Context-free grammars cannot be identified in the limit from positive examples (Gold, 1967), yet natural language grammars are more powerful than context-free grammars and humans ...
Tim Oates, Tom Armstrong, Justin Harris, Mark Nejm...
ECML
2003
Springer
13 years 9 months ago
A Hybrid Language Model based on Stochastic Context-free Grammars
Abstract. This paper explores the use of initial Stochastic Context-Free Grammars (SCFG) obtained from a treebank corpus for the learning of SCFG by means of estimation algorithms....
Diego Linares, José-Miguel Benedí, J...