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» Learning Probabilistic Models of Contours
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NN
2006
Springer
14 years 9 months ago
Propagation and control of stochastic signals through universal learning networks
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
Kotaro Hirasawa, Shingo Mabu, Jinglu Hu
RAS
2000
161views more  RAS 2000»
14 years 9 months ago
Active object recognition by view integration and reinforcement learning
A mobile agent with the task to classify its sensor pattern has to cope with ambiguous information. Active recognition of three-dimensional objects involves the observer in a sear...
Lucas Paletta, Axel Pinz
ICIP
2005
IEEE
15 years 11 months ago
Learning hidden semantic cues using support vector clustering
This paper presents a method to infer hidden semantic cues by accumulating the knowledge learned from relevance feedback sessions. We propose to explicitly represent a semantic sp...
Jia-Wen Tung, Chiou-Ting Hsu
ILP
2007
Springer
15 years 4 months ago
Learning to Assign Degrees of Belief in Relational Domains
A recurrent question in the design of intelligent agents is how to assign degrees of beliefs, or subjective probabilities, to various events in a relational environment. In the sta...
Frédéric Koriche
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
15 years 1 months ago
Learning recursive programs with cooperative coevolution of genetic code mapping and genotype
The Probabilistic Adaptive Mapping Developmental Genetic Programming (PAM DGP) algorithm that cooperatively coevolves a population of adaptive mappings and associated genotypes is...
Garnett Carl Wilson, Malcolm I. Heywood