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IJCAI
2003
14 years 14 hour ago
Constructing Diverse Classifier Ensembles using Artificial Training Examples
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Prem Melville, Raymond J. Mooney
ICML
2010
IEEE
13 years 11 months ago
Power Iteration Clustering
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Frank Lin, William W. Cohen
ICML
2010
IEEE
13 years 11 months ago
Supervised Aggregation of Classifiers using Artificial Prediction Markets
Prediction markets are used in real life to predict outcomes of interest such as presidential elections. In this work we introduce a mathematical theory for Artificial Prediction ...
Nathan Lay, Adrian Barbu
ICALT
2010
IEEE
13 years 10 months ago
Towards a Competence Based System for Recommending Study Materials (CBSR)
ā€” Most e-learning systems require intervention from a teacher. The development of adaptive hypermedia systems, such as intelligent tutoring systems, aimed to reduce the teachersā...
Athitaya Nitchot, Lester Gilbert, Gary B. Wills
ICASSP
2010
IEEE
13 years 10 months ago
Large margin filtering for Signal Sequence Labeling
Signal Sequence Labeling consists in predicting a sequence of labels given an observed sequence of samples. A naive way is to ļ¬lter the signal in order to reduce the noise and t...
Rémi Flamary, Benjamin Labbé, Alain ...