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FLAIRS
2007
13 years 11 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
SSPR
1998
Springer
14 years 25 days ago
Modified Minimum Classification Error Learning and Its Application to Neural Networks
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Hiroshi Shimodaira, Jun Rokui, Mitsuru Nakai
ICONIP
1998
13 years 10 months ago
ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm
The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...
Nikola K. Kasabov
CATA
2000
13 years 10 months ago
Neocognitron for rotated pattern recognition
Ideally computer pattern recognition systems should be insensitive to scaling, translation, distortion and rotation. Many neural network models have been proposed to address this ...
Michael Tran, Siddheswar Ray, Ronald Pose
CANDC
2009
ACM
14 years 3 months ago
A sub-symbolic model of the cognitive processes of re-representation and insight
We present a sub-symbolic computational model for effecting knowledge re-representation and insight. Given a set of data, manifold learning is used to automatically organize the d...
Dan Ventura