Global Optimization for Neural Network Training (1996)

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by Yi Shang , Benjamin W. Wah
Venue:IEEE Computer
Citations:43 - 12 self

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15 Global Search Methods For Solving Nonlinear Optimization Problems – Yi Shang - 1997
4 A Global Optimization Method for Neural Network Training – Yi Shang, Benjamin W. Wah - 1996
15 Trace-Based Methods for Solving Nonlinear Global Optimization and Satisfiability Problems – Benjamin W. Wah, Yao-jen Chang - 1996
12 Global Optimization For Constrained Nonlinear Programming – Tao Wang - 2001
6 Optimal Anytime Search For Constrained Nonlinear Programming – Yixin Chen - 2001
19 Efficient Algorithms for Function Approximation with Piecewise Linear Sigmoidal Networks – Don R. Hush, Bill Horne - 1998
21 Design of Neural Network Filters – Jan Larsen - 1993
12 Efficient Training of Feed-Forward Neural Networks – Martin Møller - 1997
1 Improving Constrained Nonlinear Search Algorithms Through Constraint Relaxation – Honghai Zhang, Honghai Zhang - 2001
6 Handling Inequality Constraints in Continuous Nonlinear Global Optimization – Tao Wang, Benjamin W. Wah - 1996
4 The Theory And Applications Of Discrete Constrained Optimization Using Lagrange Multipliers – Zhe Wu - 2000
127 Algorithms for the Satisfiability (SAT) Problem: A Survey – Jun Gu, Paul W. Purdom, John Franco, Benjamin W. Wah - 1996
66 Constructive Algorithms for Structure Learning in Feedforward Neural Networks for Regression Problems – Tin-yau Kwok, Dit-Yan Yeung - 1997
63 Trading Spaces: Computation, Representation and the Limits of Uninformed Learning – Andy Clark, Chris Thornton - 1997
1 Improving the Approximation and Convergence Capabilities of Projection Pursuit Learning – Tin-yau Kwok, Dit-Yan Yeung - 1995
7 What's Wrong with A Cascaded Correlation Learning Network: A Projection Pursuit Learning Perspective – Jenq-neng Hwang, Shih-Shien You, Shyh-rong Lay, I-Chang Jou
6 Use of Bias Term in Projection Pursuit Learning Improves Approximation and Convergence Properties – Tin-yau Kwok, Dit-Yan Yeung - 1996
Heuristics for the selection of weights in sequential feed-forward neural networks: An experimental study – Enrique Romero, Rene Alquézar - 2007
21 Constructive Feedforward Neural Networks for Regression Problems: A Survey – Tin-yau Kwok, Dit-Yan Yeung - 1995