3050 search results - page 331 / 610 » On-line Algorithms in Machine Learning |
174
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ML
2008
ACM
15 years 6 months ago
2008
ACM
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
167
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EUROCAST
2007
Springer
16 years 21 days ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
183
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ICML
2008
IEEE
16 years 7 months ago
2008
IEEE
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...
165
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ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
226
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COLT
2007
Springer
16 years 21 days ago
2007
Springer
Abstract. We study online regret minimization algorithms in a bicriteria setting, examining not only the standard notion of regret to the best expert, but also the regret to the av...