Fast Learning in Multi-Resolution Hierarchies. - John E. Moody (NIPS, 1988)

Speedy alternatives to back propagation. - John E. Moody; Christian Darken (Neural Networks, 1988)

Note on Development of Modularity in Simple Cortical Models. - Alex Chernajvsky; John E. Moody (NIPS, 1989)

Fast Learning in Networks of Locally-Tuned Processing Units. - John E. Moody; Christian J. Darken (Neural Comput., 1989)

Fast adaptive k-means clustering: some empirical results. - Christian J. Darken; John E. Moody (IJCNN, 1990)

Note on Learning Rate Schedules for Stochastic Optimization. - Christian Darken; John E. Moody (NIPS, 1990)

Towards Faster Stochastic Gradient Search. - Christian Darken; John E. Moody (NIPS, 1991)

The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems. - John E. Moody (NIPS, 1991)

Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction. - John E. Moody; Joachim Utans (NIPS, 1991)

Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria. - Todd K. Leen; John E. Moody (NIPS, 1992)

Fast Pruning Using Principal Components. - Asriel U. Levin; Todd K. Leen; John E. Moody (NIPS, 1993)

Price behavior and Hurst exponents of tick-by-tick interbank foreign exchange rates. - John E. Moody; Lizhong Wu (CIFEr, 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 (CIFEr, 1995)

A Smoothing Regularizer for Recurrent Neural Networks. - Lizhong Wu; John E. Moody (NIPS, 1995)

Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions. - John E. Moody (Neural Networks: Tricks of the Trade, 1996)

Smoothing Regularizers for Projective Basis Function Networks. - John E. Moody; Thorsteinn S. Rögnvaldsson (NIPS, 1996)

Multi-effect Decompositions for Financial Data Modeling. - Lizhong Wu; John E. Moody (NIPS, 1996)

A Smoothing Regularizer for Feedforward and Recurrent Neural Networks. - Lizhong Wu; John E. Moody (Neural Comput., 1996)

What is the "true price"? state space models for high frequency FX data. - John E. Moody; Lizhong Wu (CIFEr, 1997)

Optimization of trading systems and portfolios. - John E. Moody; Lizhong Wu (CIFEr, 1997)

Reinforcement Learning for Trading Systems and Portfolios. - John E. Moody; Matthew Saffell (KDD, 1998)

Reinforcement Learning for Trading. - John E. Moody; Matthew Saffell (NIPS, 1998)

Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting. - Yuansong Liao; John E. Moody (NIPS, 1999)

Data Visualization and Feature Selection: New Algorithms for Nongaussian Data. - Howard Hua Yang; John E. Moody (NIPS, 1999)

Learning to trade via direct reinforcement. - John E. Moody; Matthew Saffell (IEEE Trans. Neural Networks, 2001)

Stock returns: momentum, volatility and interest rates. - Yue Fang; Sakae Wada; John E. Moody (CIFEr, 2003)

Stochastic Direct Reinforcement: Application to Simple Games with Recurrence. - John E. Moody; Yufeng Liu; Matthew Saffell; Kyoungju Youn (AAAI Technical Report (2), 2004)