Suboptimal Sequential Decision Schemes With On-Line Feature Ordering
IEEE Transactions on Computers
Renyi's entropy and the probability of error
IEEE Transactions on Information Theory
Getting to know you: learning new user preferences in recommender systems
Proceedings of the 7th international conference on Intelligent user interfaces
On the Behaviour of Information Measures for Test Selection
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Enhancing Automated Test Selection in Probabilistic Networks
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Collaborative filtering by personality diagnosis: a hybrid memory- and model-based approach
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
A graph-theoretic analysis of information value
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Look versus leap: computing value of information with high-dimensional streaming evidence
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Several rules for feature selection in myopic policy are examined for solving the sequential finite classification problem with conditionally independent binary features. The main finding is that no rule is consistently superior to the others. Likewise no specific strategy for the alternating of rules seems to be significantly more efficient.