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» Network Structuring and Training Using Rule-Based Knowledge
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JCP
2007
121views more  JCP 2007»
14 years 9 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
75
Voted
SIGMOD
2010
ACM
274views Database» more  SIGMOD 2010»
15 years 2 months ago
K-isomorphism: privacy preserving network publication against structural attacks
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due ...
James Cheng, Ada Wai-Chee Fu, Jia Liu
138
Voted
ICASSP
2011
IEEE
14 years 1 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
AAAI
2006
14 years 11 months ago
Real-Time Evolution of Neural Networks in the NERO Video Game
A major goal for AI is to allow users to interact with agents that learn in real time, making new kinds of interactive simulations, training applications, and digital entertainmen...
Kenneth O. Stanley, Bobby D. Bryant, Igor Karpov, ...
FLAIRS
2004
14 years 11 months ago
Backcalculation of Airport Flexible Pavement Non-Linear Moduli Using Artificial Neural Networks
The Heavy Weight Deflectometer (HWD) test is one of the most widely used tests for assessing the structural integrity of airport pavements in a non-destructive manner. The elastic...
Kasthurirangan Gopalakrishnan, Marshall R. Thompso...