John E. Moody

According to our database, John E. Moody authored at least 27 papers between 1988 and 2004.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2004

Stochastic Direct Reinforcement: Application to Simple Games with Recurrence.

John E. Moody, Yufeng Liu, Matthew Saffell, Kyoungju Youn

Proceedings of the Artificial Multiagent Learning, 2004

2003

Stock returns: momentum, volatility and interest rates.

Yue Fang, Sakae Wada, John E. Moody

Proceedings of the 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003

2001

Learning to trade via direct reinforcement.

John E. Moody, Matthew Saffell

IEEE Trans. Neural Networks, 2001

1999

Data Visualization and Feature Selection: New Algorithms for Nongaussian Data.

Howard Hua Yang, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting.

Yuansong Liao, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

Reinforcement Learning for Trading.

John E. Moody, Matthew Saffell

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Reinforcement Learning for Trading Systems and Portfolios.

John E. Moody, Matthew Saffell

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

1997

Optimization of trading systems and portfolios.

John E. Moody, Lizhong Wu

Proceedings of the IEEE/IAFE 1997 Computational Intelligence for Financial Engineering, 1997

What is the "true price"? state space models for high frequency FX data.

John E. Moody, Lizhong Wu

Proceedings of the IEEE/IAFE 1997 Computational Intelligence for Financial Engineering, 1997

1996

A Smoothing Regularizer for Feedforward and Recurrent Neural Networks.

Lizhong Wu, John E. Moody

Neural Comput., 1996

Multi-effect Decompositions for Financial Data Modeling.

Lizhong Wu, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Smoothing Regularizers for Projective Basis Function Networks.

John E. Moody, Thorsteinn S. Rögnvaldsson

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions.

John E. Moody

Proceedings of the Neural Networks: Tricks of the Trade, 1996

1995

A Smoothing Regularizer for Recurrent Neural Networks.

Lizhong Wu, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Input variable selection for neural networks: application to predicting the U.S. business cycle.

Joachim Utans, John E. Moody, Steven Rehfuss, Hava T. Siegelmann

Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering, 1995

Price behavior and Hurst exponents of tick-by-tick interbank foreign exchange rates.

John E. Moody, Lizhong Wu

Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering, 1995

1993

Fast Pruning Using Principal Components.

Asriel U. Levin, Todd K. Leen, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria.

Todd K. Leen, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991

Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction.

John E. Moody, Joachim Utans

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems.

John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Towards Faster Stochastic Gradient Search.

Christian Darken, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990

Note on Learning Rate Schedules for Stochastic Optimization.

Christian Darken, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 3, 1990

Fast adaptive k-means clustering: some empirical results.

Christian J. Darken, John E. Moody

Proceedings of the IJCNN 1990, 1990

1989

Fast Learning in Networks of Locally-Tuned Processing Units.

John E. Moody, Christian J. Darken

Neural Comput., 1989

Note on Development of Modularity in Simple Cortical Models.

Alex Chernajvsky, John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 2, 1989

1988

Speedy alternatives to back propagation.

John E. Moody, Christian Darken

Neural Networks, 1988

Fast Learning in Multi-Resolution Hierarchies.

John E. Moody

Proceedings of the Advances in Neural Information Processing Systems 1, 1988