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IEEEICCI
2002
IEEE
14 years 14 days ago
Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly an...
Wiphada Wettayaprasit, Chidchanok Lursinsap, Chee-...
ICML
2008
IEEE
14 years 8 months ago
The dynamic hierarchical Dirichlet process
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are r...
Lu Ren, David B. Dunson, Lawrence Carin
LWA
2004
13 years 9 months ago
Learning Prototype Ontologies by Hierachical Latent Semantic Analysis
An ontology is a speci...cation of a conceptualization, a shared understanding of some domain of interest. The paper develops an algorithm that hierarchically groups words together...
Gerhard Paaß, Jörg Kindermann, Edda Leo...
AI
1998
Springer
13 years 11 months ago
Sequential Instance-Based Learning
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Susan L. Epstein, Jenngang Shih
BMCBI
2011
12 years 11 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto