Articles
- Functional Regularization, John
Moody and Thorsteinn Rognvaldsson, in preparation 2005.
- Stochastic Direct Reinforcement: Application to Simple
Games with Recurrence, John Moody, Yufeng Liu, Matthew Saffell and
Kyoungju Youn, Artificial Multiagent Learning, Sean Luke et al.
editors, AAAI Press, Menlo Park, 2004.
- Stock Returns: Momentum, Volatility and Interest Rates,
Yue Fang, Sakae Wada and John Moody,
to appear in the proceedings of Computational
Intelligence in Financial Engineering, IEEE Press, 2003.
- Learning to Trade via Direct Reinforcement, John Moody
and Matthew Saffell, IEEE Transactions on Neural Networks,
Vol. 12, No. 4, July 2001.
- Neural Networks for Time Series Analysis,Yuansong Liao,
John Moody and Lizhong Wu, in Handbook on Neural Network
Signal Processing, edited by Y-H Hu and J-N Hwang, CRC
Press 2001.
- Constructing Heterogeneous Committees via Input Feature
Grouping, Yuansong Liao and John Moody, in Advances in
Neural Information Processing Systems, Vol.12, S.A. Solla,
T.K. Leen and K.-R. Muller (eds.),MIT Press, 2000.
- Data Visualization and Feature
Selection: New Algorithms for Nongaussian Data, Howard
Yang and John Moody, in Advances in Neural Information
Processing Systems, Vol.12, S.A. Solla, T.K. Leen and
K.-R. Muller (eds.), MIT Press, 2000.
- Minimizing Downside Risk via Stochastic Dynamic Programming,
John Moody and Matthew Saffell, in Computational
Finance 1999, edited by Y. S. Abu-Mostafa, B. LeBaron, A.
W. Lo, and A. S. Weigend, MIT Press, Cambridge, MA, 2000.
- Term Structure of Interactions of Foreign Exchange Rates,
John Moody and Howard Yang, in Computational
Finance 1999, edited by Y. S. Abu-Mostafa, B. LeBaron, A.
W. Lo, and A. S. Weigend, MIT Press, Cambridge, MA, 2000.
- Reinforcement Learning for Trading, Advances in Neural
Information Processing Systems 11, M.S. Kearns, S.A. Solla
and D.A. Cohn, eds., MIT Press, Cambridge, MA 1999.
- Predicting Blood Glucose Metabolism in Diabetics -- A Machine
Learning Solution, Volker Tresp, Thomas Briegel and John Moody,
IEEE Transactions on Neural Networks, v. 10, n. 5, pp.
1204--1213, 1999.
- Feature Selection Based on Joint Mutual Information,
Howard Yang and John Moody, in Advances in Intelligent
Data Analysis (AIDA), Computational Intelligence Methods and
Applications (CIMA), International Computer Science Conventions,
Rochester, New York, June 22-25, 1999.
- Performance Functions and Reinforcement Learning for Trading
Systems and Portfolios, John Moody, Lizhong Wu, Yuansong Liao
and Matthew Saffell, Journal of Forecasting, vol. 17,
pp. 441-470, 1998.
- Forecasting the Economy with Neural Nets: A Survey of Challenges
and Solutions, John Moody, in Neural Networks: Tricks
of the Trade, Genevieve B. Orr and Klaus-Robert Muller,
eds., Springer Verlag, pp. 347-371, 1998.
- Reinforcement Learning for Trading: Immediate vs. Future
Rewards, John Moody and Matthew Saffell, Knowledge Discovery
and Datamining, Proceedings of the 1998 New York Conference,
AAAI Press, 1998.
- High Frequency Foreign Exchange Rates: Price Behavior Analysis
and `True Price' Models, John Moody and Lizhong Wu, Chapter 2
of Nonlinear Modelling of High Frequency Financial Data,
Christian Dunis and Bin Zhou, editors, Wiley Financial Publishing,
London, 1998.
- Reinforcement Learning for Trading Systems and Portfolios,
John Moody, Matthew Saffell, Yuansong Liao and Lizhong Wu,
Decision Technologies for Computational Finance, Proceedings
of the London Conference, A.N. Refenes, N. Burgess and J. Moody,
eds., Kluwer Financial Publishing, 1998.
- Stochastic Manhattan Learning: Time-Evolution Operator for the
Ensemble Dynamics, Todd Leen and John Moody, Physical Review E,
1997.
- Multi-Effect Decompositions for Financial Data Modeling,Lizhong
Wu and John Moody, in Advances in Neural Information Processing
Systems 9, M.C. Mozer, M.I. Jordan and T. Petsche, eds, MIT Press,
Cambridge, 1997.,
- Smoothing Regularizers for Projective Basis Function Networks,
John Moody and Thorsteinn Rognvaldsson, in Advances in Neural
Information Processing Systems 9, M.C. Mozer, M.I. Jordan and T.
Petsche, eds, MIT Press, Cambridge, 1997.
- Optimization of Trading Systems and Portfolios, John Moody and
Lizhong Wu, in Decision Technologies for Financial Engineering,
Y. Abu-Mostafa, A. N. Refenes, and A. S. Weigend, eds., World
Scientific, London, 1997.
- What is the True Price? -- State Space Models for High Frequency
FX Rates, John Moody and Lizhong Wu, in Decision Technologies
for Financial Engineering, Y. Abu-Mostafa, A. N. Refenes, and
A. S. Weigend, eds., World Scientific, London, 1997.
- A Smoothing Regularizer for Feedforward and Recurrent Neural
Networks, Lizhong Wu and John Moody, Neural Computation 8:3,
1996.
- Improved Estimates for the Rescaled Range and Hurst Exponents,
John Moody and Lizhong Wu, Neural Networks in Financial
Engineering, Proceedings of the Third International Conference
(London, October 1995), A. Refenes, Y. Abu-Mostafa, J. Moody,
and A. Weigend, eds., World Scientific, London, pp. 537-553,
1996.
- Trading with Committees: A Comparative Study, Steve Rehfuss,
Lizhong Wu and John Moody, Neural Networks in the Capital Markets,
Proceedings of the Third International Conference (London, October
1995), A. Refenes, Y. Abu-Mostafa, J. Moody, and A. Weigend, eds.,
World Scientific, London, 1996.
- A Neural Network Visualization and Sensitivity Analysis Toolkit,
Yuansong Liao and John Moody, Proceedings of the International
Conference on Neural Information Processing, Hong Kong, Sun-ichi
Amari, Lei Xu, Laiwan Chan, Irwin King, and Kwong-Sak Leung, eds.
Springer Verlag Singapore Pte. Ltd. pp. 1069-74, Sept. 1996.
- A Smoothing Regularizer for Feedforward and Recurrent Neural
Networks, Advances in Neural Information Processing Systems 8,
Touretzky, Mozer, and Alspector (eds), MIT Press, Cambridge,
1996.
- Macroeconomic Forecasting: Challenges and Neural Network
Solutions, John Moody, Proceedings of the International
Symposium on Artificial Neural Networks, Hsinchu, Taiwan,
1995.
- Price Behavior and Hurst Exponents of Tick-By-Tick Interbank
Foreign Exchange Rates, John Moody and Lizhong Wu, proceedings
of Computational Intelligence in Financial Engineering, IEEE
Press, 1995.
- Selecting Input Variables via Sensitivity Analysis: Application
to Predicting the U.S. Business Cycle, Joachim Utans, John Moody,
Steve Rehfuss, and Hava Siegelmann, Proceedings of Computational
Intelligence in Financial Engineering, IEEE Press, 1995.
- Statistical Analysis of Tick-by-tick Foreign Exchange Data, John
Moody and Lizhong Wu. Proceedings of the High Frequency Data in
Finance Conference, Zurich, 1995.
- Statistical Analysis and Forecasting of High Frequency Foreign
Exchange Rates, John Moody and Lizhong Wu, Proceedings of the
Neural Networks in the Capital Markets Conference, Caltech,
1994.
- Prediction Risk and Neural Network Architecture Selection,
John Moody, in From Statistics to Neural Networks: Theory and
Pattern Recognition Applications, V. Cherkassky, J.H. Friedman,
and H. Wechsler (eds), Springer-Verlag, 1994.
- Architecture Selection Strategies for Neural Networks:
Application to Corporate Bond Rating Prediction, John Moody
and Joachim Utans, in Neural Networks in the Capital Markets,
Refenes A. N. (ed), John Wiley & Sons, New York, 1994.
- Fast Pruning Using Principal Components, Asriel U. Levin,
Todd K. Leen and John E. Moody, Advances in Neural Information
Processing Systems 6, Cowan, Tesauro, and Alspector (eds),
Morgan Kaufmann Publishers, San Mateo, 1994.
- Predicting the U.S. Index of Industrial Production, John Moody,
Asriel Levin, and Steve Rehfuss, Proceedings of Parallel
Applications in Statistics and Economics '93, M. Novak (ed),
special issue of Neural Network World, vol.3 num. 6, pp. 791-794,
1993.
- Weight-Space Probability Densities and Equilibria in Stochastic
Learning, Todd K. Leen and John E. Moody, Advances in Neural
Information Processing Systems 5, Hanson, Cowan, and Giles (eds),
Morgan Kaufmann Publishers, San Mateo, 1993.
- Neural Network Modeling of Physiological Processes. V. Tresp,
J. Moody, and W.R. Delong. In Computational Learning Theory and
Natural Learning Systems - vol. 2, T. Petsche, M. Kearns, S.
Hanson, R. Rivest (eds).
Cambridge, MA: MIT Press, pp. 363--378, 1993.
- Learning Rate Schedules for Faster Stochastic Gradient Search,
Christian Darken, Joseph Chang and John Moody, Neural Networks for Signal
Processing 2 --- Proceedings of the 1992 IEEE Workshop, IEEE Press,
Piscataway, NJ, 1992.
- The Effective Number of Parameters: an Analysis of Generalization
and Regularization in Nonlinear Learning Systems, John Moody, in
Advances in Neural Information Processing Systems 4,
Moody, Hanson, and Lippmann, eds., Morgan Kaufmann, Palo Alto,
pp. 847-854, 1992.
- Towards Faster Stochastic Gradient Search, Christian Darken and
John Moody, in Advances in Neural Information Processing Systems 4,
Moody, Hanson, and Lippmann, eds., Morgan Kaufmann, Palo Alto,
1992.
- Principled Architecture Selection for Neural Networks: Application
to Corporate Bond Rating Prediction, John Moody and Joachim Utans,
in Advances in Neural Information Processing Systems 4,
Moody, Hanson, and Lippmann, eds., Morgan Kaufmann, Palo Alto,
1992.
- Networks with Learned Unit Response Functions, John Moody and Norman
Yarvin, in Advances in Neural Information Processing Systems 4,
Moody, Hanson, and Lippmann, eds., Morgan Kaufmann, Palo Alto,
pp. 1048-1055 1992.
- Note on Generalization, Regularization, and Architecture Selection
in Nonlinear Learning Systems, John E. Moody, in Proceedings of the
First IEEE-SP Workshop on Neural Networks for Signal Processing.
IEEE Computer Society Press, Los Alamitos, CA, pp. 1-10, 1991.
- Selecting Neural Network Architectures via the Prediction Risk:
Application to Corporate Bond Rating Prediction, Joachim Utans and
John Moody, in Proceedings of the First International
Conference on Artificial Intelligence Applications on Wall Street,
IEEE Computer Society Press, Los Alamitos, CA, 1991.
- Note on Learning Rate Schedules for Stochastic Optimization,
Christian Darken and John Moody, in Advances in Neural Information
Processing Systems 3, Lippmann, Moody, and Touretzky, eds.,
Morgan Kaufmann, Palo Alto, 1991.
- Spontaneous Development of Modularity in Simple Cortical Models,
Alex Chernjavsky and John Moody, Neural Computation, 2:3 p.334-354,
1990.
- Dynamics of Lateral Interaction Networks, John Moody, Proceedings
of the IEEE IJCNN Conference, San Diego, IEEE Press, Piscataway,
NJ, 1990.
- Fast, Adaptive K-Means Clustering: Some Empirical Results,
Christian Darken and John Moody, Proceedings of the IEEE IJCNN
Conference, San Diego, IEEE Press, Piscataway, NJ, 1990.
- Note on Development of Modularity in Simple Cortical Models, Alex
Chernjavsky and John Moody, Advances in Neural Information
Processing Systems 2, D. Touretzky, ed., Morgan Kaufmann, Palo Alto,
1990.
- Adiabatic Effective Lagrangian, John Moody, Alfred Shapere, and
Frank Wilczek, in Geometric Phases in Physics, edited by A. Shapere
and F. Wilczek, World Scientific Publishing Co., 1989.
- Fast Learning in Multi-Resolution Hierarchies", John Moody, in
Advances in Neural Information Processing Systems, D. Touretzky,
editor, Morgan Kauffmann, 1989.
- Fast Learning in Networks of Locally-Tuned Processing Units, John
Moody and Christian Darken, Neural Computation 1 pp. 289-303,
1989.
- Learning with Localized Receptive Fields, John Moody and Christian
Darken, Proceedings of the 1988 Connectionist Models Summer School,
Hinton, Sejnowski, and Touretzsky, eds. Morgan Kaufmann, pp. 133-143,
1988.
- Internal Representations for Associative Memory, Eric B. Baum,
John Moody, and Frank Wilczek, Biological Cybernetics 59 217-228,
1988.
- Associative Memories", John Moody, Chapter II 5, DARPA Neural Network
Study Final Report, Richard Lippmann, ed., 1988.
- Perspectives on Associative Memories", John Moody, Proceedings of
the IEEE First International Conference on Neural Networks, M.
Caudill and C. Butler, eds. pg.III-59, 1987.
- Computable Functions and Complexity in Neural Networks, Omer
Egecioglu, Terence R. Smith, and John Moody, in Real Brains, Artificial
Minds, J. L. Casti and A. Karlqvist, eds., Elsevier Science Publishing
Co, 1987.
- Macroscopic T Nonconservation: Prospects for a New Experiment,
William Bialek, John Moody, and Frank Wilczek, Physical Review Letters
56 1623, 1986.
- Realizations of Magnetic Monopole Gauge Fields: Diatoms and
Spin-Precession, John Moody, Alfred Shapere, and Frank Wilczek,
Physical Review Letters 56 893, 1986.
- Prospects for Axion Detection, John Moody, Dark Matter: Proceedings
of IAU Symposium 117, 1985.
- Calculations for Cosmic Axion Detection, Lawrence Krauss, John
Moody, Frank Wilczek, and Donald Morris, Physical Review Letters
55 1797, 1985.
- A Stellar Energy Loss Mechanism Involving Axions, Lawrence M.
Krauss, John E. Moody, and Frank Wilczek, Physics Letters 144B 391,
1984.
- Axions, Gravity Experiments and T Violation", Ph.D. Dissertation,
Princeton University, 1984.
- New Macroscopic Forces?, J.E. Moody and Frank Wilczek, Physical
Review D30 130, 1984.
- Filamentary Galaxy Clustering: A Mapping Algorithm, J.E. Moody,
Edwin L. Turner, and J. Richard Gott III, Astrophysical Journal
273 16, 1983.
- Temperature Profiles Induced by a Scanning CW Laser Beam, J.E. Moody
and R.H. Hendel, Journal of Applied Physics 53 4364, 1982.
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