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137
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FUIN
2002
132views more  FUIN 2002»
15 years 3 months ago
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
Grzegorz Góra, Arkadiusz Wojna
114
Voted
COGSCI
2011
43views more  COGSCI 2011»
14 years 10 months ago
Japanese Sound-Symbolism Facilitates Word Learning in English-Speaking Children
Sound symbolism is the non-arbitrary link between the sound of a word and its meaning. Imai et al. (2008) showed that Japanese speaking children benefited from the presence of sou...
Katerina Kantartzis, Mutsumi Imai, Sotaro Kita
147
Voted
IJCNN
2008
IEEE
15 years 10 months ago
Learning to select relevant perspective in a dynamic environment
— When an agent observes its environment, there are two important characteristics of the perceived information. One is the relevance of information and the other is redundancy. T...
Zhihui Luo, David A. Bell, Barry McCollum, Qingxia...
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
15 years 10 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
ICTAI
2008
IEEE
15 years 10 months ago
Using Imputation Techniques to Help Learn Accurate Classifiers
It is difficult to learn good classifiers when training data is missing attribute values. Conventional techniques for dealing with such omissions, such as mean imputation, general...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...