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ISMB
1993
14 years 11 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
GLVLSI
1998
IEEE
124views VLSI» more  GLVLSI 1998»
15 years 1 months ago
Non-Refreshing Analog Neural Storage Tailored for On-Chip Learning
In this research, we devised a new simple technique for statically holding analog weights, which does not require periodic refreshing. It further contains a mechanism to locally u...
Bassem A. Alhalabi, Qutaibah M. Malluhi, Rafic A. ...
ICANN
2010
Springer
14 years 10 months ago
Learning Invariant Visual Shape Representations from Physics
3D shape determines an object's physical properties to a large degree. In this article, we introduce an autonomous learning system for categorizing 3D shape of simulated objec...
Mathias Franzius, Heiko Wersing
IJCNN
2008
IEEE
15 years 4 months ago
Evolving a neural network using dyadic connections
—Since machine learning has become a tool to make more efficient design of sophisticated systems, we present in this paper a novel methodology to create powerful neural network ...
Andreas Huemer, Mario A. Góngora, David A. ...
IDEAL
2005
Springer
15 years 3 months ago
Neural Networks: A Replacement for Gaussian Processes?
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
Matthew Lilley, Marcus R. Frean