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» Evaluating learning algorithms and classifiers
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104
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AIRWEB
2007
Springer
15 years 4 months ago
Measuring Similarity to Detect Qualified Links
The early success of link-based ranking algorithms was predicated on the assumption that links imply merit of the target pages. However, today many links exist for purposes other ...
Xiaoguang Qi, Lan Nie, Brian D. Davison
ICML
2004
IEEE
16 years 1 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
117
Voted
AIME
1997
Springer
15 years 4 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
103
Voted
JMLR
2008
116views more  JMLR 2008»
15 years 14 days ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
COLT
1995
Springer
15 years 4 months ago
On the Learnability and Usage of Acyclic Probabilistic Finite Automata
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Dana Ron, Yoram Singer, Naftali Tishby