On linear programming, neural network design, pattern classification and Polynomial time training

Asim Roy

doi:10.1109/ICPR.1992.201709

On linear programming, neural network design, pattern classification and Polynomial time training

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Polynomial time training and network design are two major issues for the neural network community. A new algorithm has been developed that can both "design" an appropriate network and "train" it in polynomial time. Network design is no longer a black art. The algorithm is for classification problems and uses linear programming formulations in designing and training the network. This paper will summarize the new algorithm.

Original language	English (US)
Title of host publication	Conference B
Subtitle of host publication	Pattern Recognition Methodology and Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5-8
Number of pages	4
Volume	2
ISBN (Print)	0818629150
DOIs	https://doi.org/10.1109/ICPR.1992.201709
State	Published - Jan 1 1992
Event	11th IAPR International Conference on Pattern Recognition, IAPR 1992 - The Hague, Netherlands Duration: Aug 30 1992 → Sep 3 1992

Other

Other	11th IAPR International Conference on Pattern Recognition, IAPR 1992
Country/Territory	Netherlands
City	The Hague
Period	8/30/92 → 9/3/92

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICPR.1992.201709

Cite this

Roy, A 1992, On linear programming, neural network design, pattern classification and Polynomial time training. in Conference B: Pattern Recognition Methodology and Systems. vol. 2, 201709, Institute of Electrical and Electronics Engineers Inc., pp. 5-8, 11th IAPR International Conference on Pattern Recognition, IAPR 1992, The Hague, Netherlands, 8/30/92. https://doi.org/10.1109/ICPR.1992.201709

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ER -

On linear programming, neural network design, pattern classification and Polynomial time training

Abstract

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