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ARTMED
2006
75views more  ARTMED 2006»
13 years 9 months ago
Semi-automatic learning of simple diagnostic scores utilizing complexity measures
Objective: Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semiautoma...
Martin Atzmüller, Joachim Baumeister, Frank P...
ICMCS
2009
IEEE
97views Multimedia» more  ICMCS 2009»
13 years 7 months ago
Some new directions in graph-based semi-supervised learning
In this position paper, we first review the state-of-the-art in graph-based semi-supervised learning, and point out three limitations that are particularly relevant to multimedia ...
Xiaojin Zhu, Andrew B. Goldberg, Tushar Khot
MLDM
2005
Springer
14 years 2 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
ESANN
2004
13 years 10 months ago
An informational energy LVQ approach for feature ranking
Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a ...
Razvan Andonie, Angel Cataron
TIT
2008
76views more  TIT 2008»
13 years 9 months ago
Improved Risk Tail Bounds for On-Line Algorithms
We prove the strongest known bound for the risk of hypotheses selected from the ensemble generated by running a learning algorithm incrementally on the training data. Our result i...
Nicolò Cesa-Bianchi, Claudio Gentile