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JCP
2007
121views more  JCP 2007»
15 years 6 months ago
Learning by Discrimination: A Constructive Incremental Approach
Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...
Christophe G. Giraud-Carrier, Tony R. Martinez
JSA
1998
74views more  JSA 1998»
15 years 6 months ago
Windowed active sampling for reliable neural learning
The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive preprocessing to bridge the representation ga...
Emilia I. Barakova, Lambert Spaanenburg
ICONIP
2009
15 years 4 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
ICIP
2005
IEEE
16 years 8 months ago
Layered local prediction network with dynamic learning for face super-resolution
In this paper, we propose a novel framework for face super-resolution based on a layered predictor network. In the first layer, multiple predictors are trained online with a dynami...
Dahua Lin, Wei Liu, Xiaoou Tang
ICIP
2002
IEEE
16 years 8 months ago
Learning similarity space
In this study, we suggest a method to adapt an image retrieval system into a configurable one. Basically, original feature space of a content-based retrieval system is nonlinearly...
Abdurrahman Çarkacioglu, Fatos T. Yarman-Vu...