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NIPS
1992
15 years 25 days ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
ICSNC
2007
IEEE
15 years 6 months ago
Movement Prediction Using Bayesian Learning for Neural Networks
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...
Sherif Akoush, Ahmed Sameh
HIS
2001
15 years 1 months ago
Global Optimisation of Neural Networks Using a Deterministic Hybrid Approach
Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural...
Gleb Beliakov, Ajith Abraham
ICML
1991
IEEE
15 years 3 months ago
Constructive Induction in Knowledge-Based Neural Networks
Artificial neural networks have proven to be a successful, general method for inductive learning from examples. However, they have not often been viewed in terms of constructive ...
Geoffrey G. Towell, Mark Craven, Jude W. Shavlik
IJACTAICIT
2010
163views more  IJACTAICIT 2010»
14 years 9 months ago
Modified Vector Field Histogram with a Neural Network Learning Model for Mobile Robot Path Planning and Obstacle Avoidance
In this work, a Modified Vector Field Histogram (MVFH) has been developed to improve path planning and obstacle avoidance for a wheeled driven mobile robot. It permits the detecti...
Bahaa I. Kazem, Ali H. Hamad, Mustafa M. Mozael