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98
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IDEAL
2000
Springer
15 years 4 months ago
Quantization of Continuous Input Variables for Binary Classification
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Michal Skubacz, Jaakko Hollmén
87
Voted
TREC
2007
15 years 1 months ago
Passage Relevancy Through Semantic Relatedness
Questions that require answers in the form of a list of entities and the identification of diverse biological entity classes present an interesting challenge that required new app...
Luis Tari, Phan Huy Tu, Barry Lumpkin, Robert Leam...
88
Voted
ICML
2006
IEEE
16 years 1 months ago
Hidden process models
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
94
Voted
INFOCOM
2002
IEEE
15 years 5 months ago
Channel Sharing by Rate Adaptive Streaming Applications
There are various techniques for adapting the transmission rate of an application while maintaining the perceived quality at the receiver at acceptable levels. Shared channel syst...
Leonidas Georgiadis, Nikos Argiriou
102
Voted
IJCNN
2000
IEEE
15 years 5 months ago
Metrics that Learn Relevance
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
Samuel Kaski, Janne Sinkkonen