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NIPS
2001
15 years 1 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
GECCO
2006
Springer
169views Optimization» more  GECCO 2006»
15 years 3 months ago
An open-set speaker identification system using genetic learning classifier system
This paper presents the design and implementation of an adaptive open-set speaker identification system with genetic learning classifier systems. One of the challenging problems i...
WonKyung Park, Jae C. Oh, Misty K. Blowers, Matt B...
ICML
2002
IEEE
16 years 15 days ago
Is Combining Classifiers Better than Selecting the Best One
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
Saso Dzeroski, Bernard Zenko
ESANN
2004
15 years 1 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
74
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AAAI
2007
15 years 2 months ago
KSU Willie in Semantic Vision Challenge
The KSU Willie entry in the Semantic Vision Challenge will use a variety of classifiers, some standard classifiers and some newly developed classifiers, to learn the classificatio...
David Gustafson, Aaron Chavez, Michael Marlen, And...