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Comparing Biases for Minimal Network Construction with Back-Propagation

Neural Information Processing SystemsApr-6-2023, 19:54:01 GMT

This approach can be used to (a) dynamically select the number of hidden units. The method Rumelhart suggests involves adding penalty terms to the usual error function. In this paper we introduce Rumelhart·s minimal networks idea and compare two possible biases on the weight search space. These biases are compared in both simple counting problems and a speech recognition problem.

back-propagation, back-propagation network, minimal network construction, (2 more...)

Neural Information Processing Systems

Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.79)

Comparing Biases for Minimal Network Construction with Back-Propagation

Hanson, Stephen Jose, Pratt, Lorien Y.

Neural Information Processing SystemsDec-31-1989

This approach can be used to (a) dynamically select the number of hidden units.

artificial intelligence, machine learning, rumelhart, (17 more...)

Neural Information Processing Systems

Country: North America > United States > New Jersey > Middlesex County > New Brunswick (0.04)

Technology:

Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.96)
Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.87)

Comparing Biases for Minimal Network Construction with Back-Propagation

Hanson, Stephen Jose, Pratt, Lorien Y.

Neural Information Processing SystemsDec-31-1989

This approach can be used to (a) dynamically select the number of hidden units.

artificial intelligence, machine learning, rumelhart, (17 more...)

Neural Information Processing Systems

Country: North America > United States > New Jersey > Middlesex County > New Brunswick (0.04)

Technology:

Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.96)
Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.87)

Comparing Biases for Minimal Network Construction with Back-Propagation

Hanson, Stephen Jose, Pratt, Lorien Y.

Neural Information Processing SystemsDec-31-1989

This approach can be used to (a) dynamically select the number of hidden units.

artificial intelligence, machine learning, rumelhart, (17 more...)

Neural Information Processing Systems

Country: North America > United States > New Jersey (0.05)

Technology:

Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.96)
Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.87)