Sciweavers

248 search results - page 33 / 50
» Adapting RBF Neural Networks to Multi-Instance Learning
Sort
View
TNN
2008
178views more  TNN 2008»
13 years 7 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
CEC
2007
IEEE
14 years 2 months ago
Evolving neuromodulatory topologies for reinforcement learning-like problems
— Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advanta...
Andrea Soltoggio, Peter Dürr, Claudio Mattius...
CEC
2007
IEEE
14 years 2 months ago
Combine and compare evolutionary robotics and reinforcement Learning as methods of designing autonomous robots
—The purpose of this paper is to present a comparison between two methods of building adaptive controllers for robots. In spite of the wide range of techniques which are used for...
Sergiu Goschin, Eduard Franti, Monica Dascalu, San...
NN
2002
Springer
125views Neural Networks» more  NN 2002»
13 years 7 months ago
Generalized relevance learning vector quantization
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
Barbara Hammer, Thomas Villmann
ICDM
2003
IEEE
119views Data Mining» more  ICDM 2003»
14 years 28 days ago
A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering
Clustering by document concepts is a powerful way of retrieving information from a large number of documents. This task in general does not make any assumption on the data distrib...
Chihli Hung, Stefan Wermter