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» Training Methods for Adaptive Boosting of Neural Networks
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ICRA
2000
IEEE
85views Robotics» more  ICRA 2000»
15 years 2 months ago
Neural Network Controller for Constrained Robot Manipulators
In this paper, a neural network controller for constrained robot manipulators is presented. A feedforward neural network is used to adaptively compensate for the uncertainties in ...
Shenghai Hu, Marcelo H. Ang, Hariharan Krishnan
AI
2002
Springer
14 years 9 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
CSSE
2008
IEEE
15 years 4 months ago
Application of New Adaptive Higher Order Neural Networks in Data Mining
This paper introduces an adaptive Higher Order Neural Network (HONN) model and applies it in data mining such as simulating and forecasting government taxation revenues. The propo...
Shuxiang Xu, Ling Chen
ICPR
2010
IEEE
15 years 2 months ago
Active Boosting for Interactive Object Retrieval
This paper presents a new algorithm based on boosting for interactive object retrieval in images. Recent works propose ”online boosting” algorithms where weak classifier sets...
Alexis Lechervy, Philippe Henri Gosselin, Frederic...
85
Voted
EVOW
2007
Springer
15 years 3 months ago
An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA)...
Ferrante Neri, Niko Kotilainen, Mikko Vapa