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» Combinations of Weak Classifiers
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ICASSP
2008
IEEE
14 years 3 months ago
Bringing diverse classifiers to common grounds: dtransform
Several classification scenarios employ multiple independently trained classifiers and the outputs of these classifiers need to be combined. However, since each of the trained ...
Devi Parikh, Tsuhan Chen
GECCO
2006
Springer
196views Optimization» more  GECCO 2006»
14 years 9 days ago
An anticipatory approach to improve XCSF
XCSF is a novel version of learning classifier systems (LCS) which extends the typical concept of LCS by introducing computable classifier prediction. In XCSF Classifier predictio...
Amin Nikanjam, Adel Torkaman Rahmani
ESANN
2004
13 years 10 months ago
Online policy adaptation for ensemble classifiers
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of usin...
Christos Dimitrakakis, Samy Bengio
COLING
2008
13 years 10 months ago
Weakly Supervised Supertagging with Grammar-Informed Initialization
Much previous work has investigated weak supervision with HMMs and tag dictionaries for part-of-speech tagging, but there have been no similar investigations for the harder proble...
Jason Baldridge
CP
2009
Springer
14 years 9 months ago
Weakly Monotonic Propagators
Abstract. Today's models for propagation-based constraint solvers require propagators as implementations of constraints to be at least contracting and monotonic. These models ...
Christian Schulte, Guido Tack