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AAAI
1996
15 years 1 months ago
Building Classifiers Using Bayesian Networks
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Nir Friedman, Moisés Goldszmidt
112
Voted
GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
15 years 1 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
85
Voted
SIGMOD
2010
ACM
224views Database» more  SIGMOD 2010»
15 years 24 days ago
GDR: a system for guided data repair
Improving data quality is a time-consuming, labor-intensive and often domain specific operation. Existing data repair approaches are either fully automated or not efficient in int...
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Nevi...
95
Voted
COGSCI
2010
103views more  COGSCI 2010»
15 years 21 days ago
A Computational Account of the Development of the Generalization of Shape Information
Abecassis, Sera, Yonas, and Schwade (2001) have shown that young children represent shapes more metrically, and perhaps more holistically, than do older children and adults. How d...
Leonidas A. A. Doumas, John E. Hummel
153
Voted
IDA
2008
Springer
15 years 20 days ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev