[2] "A novel series expansion for the multivariate normal probability integrals based on Fourier series", Hatem Fayed and Amir Atiya, Mathematics of Computation, Vol. 83, No. 289, pp. 2385 - 2402, September 2014.

[3] "An evaluation of the integral of the product of the error function and the normal probability density, with application to the bivariate normal integral", Hatem Fayed and Amir F. Atiya, Mathematics of Computation, Vol. 83, No. 285, pp. 235–250, January 2014.

[4] "Dynamic pricing for hotel revenue management using price multipliers", Abd El-Moniem Bayoumi, Mohamed Saleh, Amir Atiya, and Heba Abdel Aziz, Journal of Revenue & Pricing Management, Vol. 12, No. 3, pp. 271-285, 2013.

[5] "A mixed breadth-depth first strategy for the branch and bound tree of Euclidean k-center problems", Hatem Fayed and Amir F. Atiya, Computational Optimization and Applications, Vol. 54, No. 3, pp. 675-703, 2013.

[6] "Parameter estimation for coupled tank using estimate filtering", Jihoon Seung, Amir F. Atiya, Alexander G. Parlos, and Kilto Chong, International Journal of Control and Automation, Vol. 6, No. 5, pp.91-102, 2013.

[7] "A novel quota sampling algorithm for generating representative random samples given small sample size", Ahmed M. Fouad, Mohamed Saleh, Amir F. Atiya, International Journal of System Dynamics Applications (IJSDA), Vol. 2, No. 1, pp. 97-113, 2013.

[8] "A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition", S. Ben Taieb, G. Bontempi, A. Atiya, and A. Sorjamaa, Expert Systems with Applications, Vol. 39, No. 8, pp. 7067-7083, 2012.

[9] "Parameter estimation of 2-DOF system based on unscented Kalman filter", J. Seung, T. Kim, A. Atiya, A. G. Parlos, and K. T. Chong, Journal of the Korean Society for Precision Engineering, Vol. 29, No. 10, pp. 1128-1146, October 2012.

[10] "Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances", A. Khosravi, S. Nahavandi, D. Creighton, and A. F. Atiya, IEEE Transactions on Neural Networks, Vol. 22, No. 9, 1341 - 1356, September 2011.

[11] "A lower upper bound estimation method for construction of neural network-based prediction intervals", A. Khosravi, S. Nahavandi, D. Creighton, and A. F. Atiya, IEEE Transactions on Neural Networks, Vol. 22, No. 3, pp. 337-346, March 2011.

[12] "Forecast combination model using computational intelligence/linear models for the NN5 time series forecasting competition", Robert Andrawis, Amir F. Atiya, Hisham El-Shishiny, International Journal of Forecasting, Vol. 27, No. 3, pp. 672-688, 2011.

[13] "Forecasting hotel arrivals and occupancy using Monte Carlo simulation", Athanasius Zakhary, Amir Atiya, Hisham El-Shishiny, and Neamat El Gayar, Journal of Revenue & Pricing Management, Vol. 10, No. 4, pp. 344-366, 2011.

[14] "Combination of long Term and short term forecasts, with application to tourism demand forecasting", Robert Andrawis, Amir F. Atiya, and Hisham El-Shishiny, International Journal of Forecasting, Vol. 27, No. 3, pp. 870-886, 2011.

[15] "UKF parameter estimation of dynamic system based on experimental data", J. Seung, T. Kim, A. Atiya, A. G. Parlos, and K. T. Chong, Journal of the Korean Society for Precision Engineering, Vol. 26, No. 1, pp. 1-9, January 2011.

[16] "Case Study: An Integrated Framework for advanced Hotel Revenue Management", N. El Gayar, M. Saleh, A. Atiya, H. El-Shishiny, A. Zakhary and H. Abdel Aziz, International Journal of Contemporary Hospitality Management, Vol. 23, No. 1, January 2011.

[17] "An empirical comparison of machine learning models for time series forecasting", Nesreen K. Ahmed, Amir F. Atiya, Neamat El Gayar, and Hisham El-Shishiny, Econometric Reviews, Vol. 29, No. 5-6, 2010.

[18] "Solution of systems of Boolean equations via the integer domain", Ahmed H. Abdel-Gawad, Amir F. Atiya, Nevin M. Darwish, Information Sciences, Vol. 180 pp. 288–300, January 2010.

[19] "A new Bayesian formulation for Holt's exponential smoothing", Robert Andrawis and Amir F. Atiya, Journal of Forecasting, Vol. 28, No. 3, pp. 218-234, April 2009.

[20] "A Penalized Likelihood based Pattern Classification Algorithm", Amir F. Atiya and Ahmed Al-Ani, Pattern Recognition, Volume 42, pp. 2684 – 2694, 2009.

[21] "A novel template reduction approach for the K-nearest neighbor method", Hatem Fayed and Amir Atiya, IEEE Transactions on Neural Networks, pp. 890-896, May 2009.

[22] "An analytic approximation of the likelihood function for the Heston model volatility estimation problem", Amir Atiya and Steve Wall, Quantitative Finance, Vol. 9, No. 3, pp. 289–296, April 2009.

[23] "Novel ensemble techniques for regression with missing data", Mostafa Hassan, Amir Atiya, Neamat El Gayar, and Raafat El-Fouly, New Mathematics and Natural Computation, Vol. 5, No. 3, pp. 635-652, 2009.

[24] "Symbolic function network", George Eskander and Amir Atiya, Neural Networks, Vol. 22, No. 4, pp. 395-404, 2009.

[25] "Hyperspherical prototypes for pattern classification", Hatem Fayed, Amir Atiya, and Sherif Hashem, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 23, No. 8, pp. 1549-1575, 2009.

[26] "A neural network based dynamic forecasting model for trend impact analysis", Nedaa Agami, Amir Atiya, Mohamed Saleh, and Hisham El-Shishiny, Technological Forecasting & Social Change, Vol. 76, 952–962, 2009.

[27] "A comparative study of the pickup method and its variations using a simulated hotel reservation data", Athanasius Zakhary, Neamat El Gayar, and Amir F. Atiya, International Journal of Artificial Intelligence and Machine Learning, Vol. 8, pp. 15-21, 2008.

[28] "Packet loss rate prediction using the sparse basis prediction model", Amir F. Atiya, Sung Goo Yoo, Kil To Chong, and Hyongsuk Kim, IEEE Transactions on Neural Networks, Vol. 18, No. 3, pp. 950-954, May 2007.

[29] " Self-generating prototypes for pattern classification", Hatem Fayed, Sherif Hashem, and Amir Atiya, Pattern Recognition, Vol. 40, pp. 1498-1509, 2007.

[30] "Novel methods for the feature subset ensembles approach", Mohamed Aly and Amir Atiya, International Journal of Artificial Intelligence and Machine Learning, Vol. 6, No. 4, 2006.

[31] "Efficient estimation of first passage time density function for jump diffusion processes", Amir Atiya and Steve Metwally, SIAM Journal of Scientific Computing, Vol. 26, No. 5, pp. 1760-1775, 2005.

[32] "Sparse basis selection: new results and application to adaptive prediction of video source traffic", Amir F. Atiya, Mohamed Aly, and Alexander G. Parlos, IEEE Transactions on Neural Networks, Vol. 16, No. 5, pp. 1136-1146, September 2005.

[33] "Guest editorial: introduction to the special issue on adaptive learning systems in communications networks", A. Parlos, C. Ji, T. Parisini, M. Baglietto, A. Atiya, and K. Claffy, IEEE Transactions on Neural Networks, Vol. 16, No. 5, pp. 1013-1018, September 2005.

[34] "Estimating the posterior probabilities using the K-nearest neighbor rule", Amir Atiya, Neural Computation, Vol. 17, No. 3, pp. 731-740, March 2005.

[35] "Maximum drawdown", Malik Magdon-Ismail and Amir Atiya, Risk Magazine, October 2004.

[36] "On the maximum drawdown of a Brownian motion", Malik Magdon-Ismail, Amir Atiya, Amrit Pratap, and Yaser Abu-Mostafa, Journal of Applied Probability, Volume 41, Number 1, March, 2004.

[37] "Prediction of MPEG-coded video source traffic using recurrent neural networks", Aninda Bhattacharya, Alexander Parlos, and Amir Atiya, IEEE Transactions Signal Processing, Vol.51, No.8, 2003.

[38] "A maximum likelihood approach to volatility estimation for a Brownian motion using the high, low and close", Malik Magdon-Ismail and Amir Atiya, Quantitative Finance, volume 3, issue 5, pages 376 - 384, 2003.

[39] "Density estimation and random variate generation using multilayer networks", Malik Magdon-Ismail and Amir Atiya, IEEE Transactions Neural Networks, Vol. 13, No. 3, pp. 497-520, May 2002.

[40] "Using the Brownian bridge for fast simulation of jump-diffusion processes and barrier options", Steve Metwally and Amir Atiya, Journal of Derivatives, pp. 43-54, Fall 2002.

[41] "An adaptive state filtering algorithm for systems with partially known dynamics", Alexander Parlos, Sunil Menon, and Amir Atiya, ASME Journal of Dynamic Systems, Measurement and Control, Vol. 124, pp. 364-374, September 2002.

[42] "Guest Editorial: Special Issue on Neural Networks in Financial Engineering", Y. Abu-Mostafa, A. Atiya, M. Magdon-Ismail, and H. White, IEEE Transactions on Neural Networks, Vol. 12, No. 4, pp. 653-656, July 2001.

[43] "Bankruptcy prediction for credit risk using neural networks: a survey and new results", Amir Atiya, IEEE Transactions on Neural Networks, Vol. 12, No. 4, pp. 929-935, July 2001.

[44] "An algorithmic approach to adaptive state filtering using recurrent neural networks", Alexander Parlos, Sunil Menon, and Amir Atiya, IEEE Transactions Neural Networks, Vol. 12, No. 6, pp. 1411-1432, November 2001.

[45] "Neuro-predictive process control using on-line controller adaptation", Sanjay Parthasarathy, Alexander Parlos, and Amir Atiya, IEEE Transactions Control Systems Technology, Vol. 9, No. 5, pp. 741-755, September 2001.

[46] "New results on recurrent network training: unifying the algorithms and accelerating convergence", Amir Atiya and Alexander Parlos, IEEE Transactions Neural Networks, Vol. 11, No. 3, pp. 697-709, May 2000.

[47] "The early restart algorithm", Malik Magdon-Ismail and Amir Atiya, Neural Computation, Vol. 12, No. 6, pp. 1303-1312, June 2000.

[48] "A new algorithm for learning in piecewise-linear neural networks", Emad Gad, Amir Atiya, Samir Shaheen, and Ayman El-Dessouky, Neural Networks, Vol. 13, No. 4-5, pp. 485-505, May/June 2000.

[49] "Multi-step-ahead prediction in complex systems using dynamic recurrent neural networks", Alexander Parlos, Omar Rais, and Amir Atiya, Neural Networks, Vol. 13, No. 7, pp. 765-786, September 2000.

[50] "Three-dimensional video compression using subband/wavelet transform with lower buffering requirements", Hosam Khalil, Amir Atiya, and Samir Shaheen, IEEE Transactions Image Processing, Vol. 8, No. 6, pp. 762-773, June 1999.

[51] "A comparison between neural network forecasting techniques - case study: river flow forecasting", Amir Atiya, Suzan El-Shoura, Samir Shaheen, and Mohamed El-Sherif, IEEE Transactions Neural Networks, Vol. 10, No. 2, pp. 402-409, March 1999.

[52] "How initial conditions affect generalization performance in large networks", Amir Atiya and Chuanyi Ji, IEEE Trans. Neural Networks, Vol.8, No. 2, pp. 448-451, March 1997.

[53] " "Introduction to financial forecasting", Yaser Abu-Mostafa and Amir Atiya, Applied Intelligence, Vol. 6, pp. 205-213, 1996.

[54] "Identification of nonlinear dynamics using a general spatio-temporal network", Amir Atiya and Alexander Parlos, Mathematical and Computer Modeling Journal, Vol. 21, No. 1, pp. 53-71, January 1995.

[55] "How delays affect neural dynamics and learning", Pierre Baldi and Amir Atiya, IEEE Trans. Neural Networks, Vol. 5, No. 4, pp. 612-621, July 1994.

[56] "Application of the recurrent multilayer perceptron in modeling complex process dynamics", A. Parlos, K. Chong, and A. Atiya, IEEE Trans. Neural Networks, Vol. 5, No. 2, pp. 255-266, March 1994.

[57] "An accelerated learning algorithm for backpropagation networks", A. Parlos, B. Fernandez, A. Atiya, J. Muthusami, and W. Tsai, IEEE Trans. Neural Networks, Vol. 5, No. 3, pp. 493-497, May 1994.

[58] "Incipient fault detection and identification in process systems using accelerated neural network learning", A. Parlos, J. Muthusami, and A. Atiya, Nuclear Technology, Vol. 105, No. 2, pp. 145-161, February 1994.

[59] "Empirical model development and validation with dynamic learning in the recurrent multilayer perceptron", A. Parlos, K. Chong, and A. Atiya, Nuclear Technology, Vol. 105, No. 2, pp. 271-290, February 1994.

[60] "An analog feedback associative memory", Amir Atiya and Yaser Abu-Mostafa, IEEE Trans. Neural Networks, Vol. 4, No. 1, pp. 117-126, January 1993.

[61] "Recognition of multiunit neural signals", Amir Atiya, IEEE Trans. Biomedical Engineering, Vol. 39, No. 7, pp. 723-729, July 1992.

[62] "Nonlinear identification of process dynamics using neural networks", A. Parlos, A. Atiya, K. Chong, and W. Tsai, Nuclear Technology, January 1992.

[63] "An unsupervised learning technique for artificial neural networks", Amir Atiya, Neural Networks, Vol. 3, No. 6, pp. 707-711, 1990.

[64] "Oscillations and synchronizations in neural networks: an exploration of the labeling hypothesis", Amir Atiya and Pierre Baldi, International Journal of Neural Systems, Vol. 1, No. 2, pp. 103-124, 1989.

[65] "Learning without a teacher in neural networks", (in German) Amir Atiya, Design \& Elektronik, March 21, 1989.

[66] "The optimal linear feature for the three-class equal-covariance Gaussian case", Amir Atiya and Talaat El-Sheikh, IEEE Trans. Systems, Man, Cybernetics, Vol. SMC-17, No. 3, pp. 495-502, 1987.

[1] "Forecast combination strategies for handling structural breaks for time series forecasting", Waleed Azmy, Amir Atiya, and Hisham El-Shishiny, Proceedings Workshop on Multiple Classifier Systems (MCS'10), Cairo, Egypt, 2010.

[2] "A new Monte Carlo-based error rate estimator", Ahmed S. Hefny, and Amir F. Atiya, Proceedings Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Cairo, Egypt, F. Schwenker and N. El Gayar, Eds. Springer Subseries of Lecture Notes in Computer Science, pp. 37-47, 2010.

[3] "Pattern classification using a penalized likelihood method", Ahmed Al-Ani and Amir Atiya, Proceedings Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Cairo, Egypt, F. Schwenker and N. El Gayar, Eds. Springer Subseries of Lecture Notes in Computer Science, pp. 197-206, 2010.

[4] "A modified K-nearest neighbor classifier to deal with unbalanced classes", Akram AlSukker, Ahmed Al-Ani, and Amir F. Atiya, Proceedings International Joint Conference on Computational Intelligence (IJCCI), Madeira, Portugal, 408-413, 2009.

[5]"Corner-based background segmentation using adaptive resonance theory", Stefano Maludrottu and Carlo S. Regazzoni and Hany Sallam and Ihab Talkhan and Amir Atiya, Proceedings International Conference on Image Processing (ICIP'09), Cairo, Egypt, 2009.

[6] "MLP, Gaussian processes and negative correlation learning for time series prediction", Waleed M. Azmy, Neamat Gayar, Amir F. Atiya, Hisham El-Shishiny, Proceedings 8th International Workshop on Multiple Classifier Systems (MCS '09), Reykjavik, Iceland, Springer-Verlag, June 2009.

[7] "Fuzzy Gaussian process classification model", Eman Ahmed, Neamat El Gayar, Amir F. Atiya, and Iman A. Azab, Proceedings of the 6th International Conference on Image Analysis and Recognition (ICIAR '09), Springer-Verlag, July 2009.

[8] "DS: A disperse swarm algorithm", Hassan Shaheen and Amir Atiya, Proceedings International Conference on Research Challenges in Computer Science, Shanghai, China, 2009.

[9] "Hand-drawn shape recognition using the SVM'ed kernel", Khaled S. Refaat and Amir F. Atiya , Proceedings 19th International Conference on Artificial Neural Networks (ICANN'09), Cyprus, Springer-Verlag, 2009.

[10] "Cerberus: applying supervised and reinforcement learning techniques to capture the flag games", Ahmed S. Hefny, Ayat A. Hatem, Mahmoud M. Shalaby, Amir F. Atiya, Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference (AAIIDE-2008), Stanford, California, the AAII Press, 2008.

[11] "A new approach for context-independent hand-written offline diagram recognition using support vector machines ". K. S. Refaat, W. Helmy, A. Ali, M. Abdelghany, A. Atiya, Proceedings of the International Joint Conference on Neural Networks (IJCNN'08), Hong Kong, China, 2008.

[12] "A new accurate approximation for the Gaussian process classification problem", Ahmed H. Abdel-Gawad and Amir F. Atiya. Proceedings of the International Joint Conference on Neural Networks (IJCNN'08), Hong Kong, China, 2008.

[13] "A new approach for room revenue maximization using advanced forecasting and optimization methods", N. El Gayar., A. Zakhary, H. Abdel Aziz, M. Saleh, A. Atiya and H. El-Shishiny, Proceedings of the EuroCHRIE Conference, Dubai, UAE, 2008.

[14] "Evolving neural networks ensembles NNEs", Hany Sallam, Carlo S. Regazzoni, Ihab Talkhan, and Amir Atiya, Proceedings 1st IAPR Workshop on Cognitive Information Processing, Santorini, Greece, 2008.

[15] "The effect of genetic operations on the diversity of evolvable neural networks", Hany Sallam, Carlo S. Regazzoni, Ihab Talkhan, and Amir Atiya, Proceedings IADIS International Conference Intelligent Systems and Agents, Amsterdam, The Netherlands, 2008.

[16] "Evolvable neural networks ensembles for accidents diagnosis", Hany Sallam, Carlo S. Regazzoni, Ihab Talkhan, and Amir Atiya, Proceeding 12th WSEAS International Conference on Computers (ICCOMP'08), Heraklion, Greece, 2008.

[17] "Measuring the genotype diversity of evolvable neural networks", Hany Sallam, Carlo S. Regazzoni, Ihab Talkhan, and Amir Atiya, Proceedings 6th International Conference on Informatics and Systems (INFOS'08), Cairo, Egypt, 2008.

[18] "A new multidimensional penalized likelihood regression method", Mostafa Hassan, Amir Atiya, and Raafat El-Fouly, Proceedings International Joint Conference on Neural Networks (IJCNN'08), Hong Kong, China, 2008.

[19] "Round trip time prediction using the symbolic function network approach", George S. Eskander, Amir Atiya, Kil To Chong, Hyongsuk Kim, and Sung Goo Yoo, Proceedings of the 2007 International Symposium on Information Technology Convergence (ISITC '07), Jeonju, South Korea, IEEE Computer Society, 2007.

[20] "A novel symbolic type neural network model- application to river flow forecasting", George S. Eskander and Amir F. Atiya, Proceedings International Computer Engineering Conference (ICENCO'07), Cairo, Egypt, 2007.

[21] "A novel approach for image compression using matching pursuit signal approximation and simulated annealing", Ahmed M. Amin, Samir I. Shaheen, Amir Atiya, Proceedings of 2007 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT '07), Cairo, Egypt, 2007.

[22] "A co-training approach for time series prediction with missing data", Tawfik A. Mohamed, Neamat El Gayar, Amir F. Atiya, Proceedings of the 7th international conference on Multiple classifier systems (MCS'07), Prague, Czech Republic, Springer-Verlag, 2007.

[23] "Regression in the presence missing data using ensemble methods", Mostafa M. Hassan, Amir F. Atiya, Neamat El Gayar, and Raafat El-Fouly, Proceedings International Joint Conference on Neural Networks (IJCNN'07), Orlando, USA, 2007.

[24] "Neural network vs. linear models for stock market sectors forecasting", Ghada Abdelmouez, Sherif Hashem, Amir F. Atiya, and Mohamed A. El-Gamal, Proceedings International Joint Conference on Neural Networks (IJCNN'07), Orlando, USA, 2007.

[25] "Comparing the performance of learnable evolution model LEM and pattern search as a function optimizer", I. Talkhan, A. F. Atiya, H. Sallam, M. Ashour, A. M. Abd El Salam, and C. S. Regazzoni, Proceedings ITI's 4th International Conference on Information & Communications Technology (ICICT '06), Cairo, Egypt, 2006.

[26] "Analysis and insights into the variable selection problem", Amir F. Atiya, Proceedings 13th International Conference on Neural information processing, ICONIP, Hong Kong, China, 2006.

[27] "Pattern classification using a set of compact hyperspheres", Amir F. Atiya, Sherif Hashem, and Hatem A. Fayed, Proceedings 13th International Conference on Neural information processing, ICONIP, Hong Kong, China, 2006.

[28] "New hyperspheres for pattern classification", Hatem Fayed, Sherif Hashem, and Amir Atiya, Proceedings 1st International Computer Engineering Conference (ICENCO-2004), Cairo, Egypt, December 2004.

[29] "The effect of individual input performance and correlations in the subset selection problem", Amir Atiya, Proceedings 1st International Computer Engineering Conference (ICENCO-2004), Cairo, Egypt, December 2004.

[30] "Fast Monte Carlo valuation of barrier options for jump diffusion processes", Steve Metwally and Amir Atiya, Proceedings IEEE Conference on Computational Intelligence in Financial Engineering (CIFER), Hong Kong, March 2003.

[31] "A reinforcement learning method based on adaptive simulated annealing", A. Atiya, A. Parlos, and L. Ingber, Proceedings IEEE Midwest Symp. Circuits Systems, Cairo, Egypt, December 2003.

[32] "Video source traffic flow prediction using neural networks", A. Bhattacharya, A. Parlos, and A. Atiya, Proceedings IEEE Midwest Symp. Circuits Systems, Cairo, Egypt, December 2003.

[33] "The maximum drawdown of the Brownian motion", M. Magdon-Ismail, A. Atiya, A. Pratap, and Y. Abu-Mostafa, Proceedings IEEE Conference on Computational Intelligence in Financial Engineering (CIFER), Hong Kong, March 2003.

[34] "State filtering with identified error dynamics and dynamic networks" A. Parlos, S. Menon, and A. Atiya, Proc 2001 IEEE International Joint Conference on Neural Network (IJCNN), Washington, DC, July 2001.

[35] "Using high, low, and close data for volatility estimation", Amir Atiya and Malik Magdon-Ismail, Proc 16th IMACS World Congress, Lausanne, Switzerland, August 2000.

[36] "Pricing the quality option for the bond futures contract in a multifactor Vasicek framework", Malik Magdon-Ismail, Amir Atiya and Yaser Abu-Mostafa, Proc 16th IMACS World Congress, Lausanne, Switzerland, August 2000.

[37] "Fast algorithms for computing corporate default probabilities", Amir Atiya, Proc. Intelligent Data Engineering and Learning Conf. (IDEAL'2000), Hong Kong, pp. 239-243, December 2000.

[38] "Some results regarding estimation of densities and random variate generattion using neural networks", Malik Magdon-Ismail and Amir Atiya, Tech Report, California Institute of Technology, Pasadena, September 2000.

[39] "Nonlinear state filtering for fault diagnosis and prognosis in complex systems using recurrent neural networks", S. K. Menon, A. G. Parlos, and A. F. Atiya, Proc 4th Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS'2000, Budapest, Hungary, June 2000.

[40] "An equity-based neural network loan default prediction model", Amir Atiya and Pratap Sondhi, Proceedings Computational Finance/ Forecasting Financial Markets Conf CF/FFM-2000, London, UK, May 2000 (Abstract only).

[41] "Volatility estimation using high, low and close data - a maximum likelihood approach", Malik Magdon-Ismail and Amir Atiya, Proceedings Computational Finance/ Forecasting Financial Markets Conf. CF/FFM-2000, London, UK, May 2000.

[42] "Neuro-predictive process control using on-line controller adaptation", A. Parlos, S. Parthasarathy, and A. Atiya, Proc American Control Conference, ACC'2000, Chicago, IL, June 2000.

[43] "A control theory formulation for random variate generation", Malik Magdon-Ismail and Amir Atiya, Proc. IEEE Workshop on Neural Networks for Signal Processing NNSP-99, Madison, Wisconsin, August 1999.

[44] "On training piecewise linear networks", Amir Atiya, Emad Gad, Samir Shaheen, and Ayman El-Dessouky, Proc. IEEE Workshop on Neural Networks for Signal Processing NNSP-99, Madison, Wisconsin, August 1999.

[45] "Lowering buffering requirements of 3-D wavelet transform coding of interactive video", Hosam Khalil, Amir Atiya, and Samir Shaheen, Proceedings IEEE Int. Conf. Image Processing, ICIP-99, Kobe, Japan, October 1999.

[46] "Trading system design using neural networks", Amir Atiya, Invited Talk, Proceedings Int. Joint Conf. Neural Networks, IJCNN-99, (Abstract only), Washington, DC, July 1999.

[47] "Multi-step-ahead prediction using dynamic recurrent neural networks", A. G. Parlos, O. T. Rais, and A. F. Atiya, Proceedings Int. Joint Conf. Neural Networks IJCNN-99, Washington, DC, July 1999.

[48] "Adaptive state estimation using dynamic recurrent neural networks", A. G. Parlos, S. K. Menon, and A. F. Atiya, Proceedings Int. Joint Conf. Neural Networks IJCNN-99, Washington, DC, July 1999.

[49] "A Bayesian approach to estimating mutual fund returns", Amir Atiya and Malik Magdon-Ismail, Proceedings Computational Finance Conf. CF-99, New York, January 1999.

[50] "Neural networks for density estimation", Malik Magdon-Ismail and Amir Atiya, in Proceedings Neural Information Processing Systems Conf NIPS-98, Denver, Colorado, November 1998.

[51] "An efficient training algorithm for piecewise linear networks", Emad Gad, Amir Atiya, Samir Shaheen, and Ayman El-Dessouky, Proc. Intelligent Data Engineering and Learning Conf. (IDEAL'98), pp. 73-79, Hong Kong, October 1998.

[52] "Neural networks for density estimation in financial markets", Malik Magdon-Ismail and Amir Atiya, Proc. Intelligent Data Engineering and Learning Conf. (IDEAL'98), pp. 171-178, Hong Kong, October 1998.

[53] "Neural networks in forecasting models: Nile River application", S. El-Shoura, M. El-Sherif, A. Atiya, and S. Shaheen, Proceedings Midwest Symposium on Circuits and systems, South Bend, IN, August 1998.

[54] "A practical gated expert network", Amir Atiya, Rasha Aiyad, and Samir Shaheen, Proc. 1998 IEEE International Joint Conference on Neural Network (IJCNN), pp. I-419-424, Alaska, May 1998.

[55] "An accelerated recurrent network training algorithm", Amir Atiya and Alexander Parlos, Proc. 1998 IEEE International Joint Conference on Neural Network (IJCNN), pp. II-1101-1106, Alaska, May 1998.

[56] "An efficient stock market forecasting model using neural networks", Amir Atiya, Noha Talaat, and Samir Shaheen, Proc. Int. Conf. Neural Networks (ICNN), Houston, June 1997.

[57] "Application of neural networks to the problem of forecasting the flow of the River Nile", Amir Atiya, Suzan El-Shoura, Samir Shaheen, and Mohamed El-Sherif, Proc. IEEE Workshop on Neural Networks for Signal Processing NNSP-97, Florida, September 1997.

[58] "Design of time-variable stop losses and profit objectives using neural networks", Amir Atiya, Proc. Fourth International Conference on Neural Networks in the Capital Markets NNCM, Pasadena, CA, November 1996.

[59] "DCT of spatially adaptive subsampled interframes for image sequence coding", Hosam Khalil, Amir Atiya and Samir Shaheen, Proc. IEEE Int. Conf. on Image Processing (ICIP-96), September 1996.

[60] "River flow forecasting using neural networks", Amir Atiya, Suzan El-Shoura, Samir Shaheen, and Mohamed El-Sherif, Proc. World Congress on Neural Networks, San Diego, CA, September 1996.

[61] "Development of an intelligent long-term electric load forecasting system", A. Parlos, E. Oufi, J. Muthusami, A. Patton, and A. Atiya, Proc. Intelligent Systems Applications to Power Systems Conference, ISAP-96, pp. 288-292, January 1996.

[62] "An analysis of stops and profit objectives in trading systems", Amir Atiya, Proc. Third International Conference on Neural Networks in the Capital Markets NNCM, London, U.K., October 1995.

[63] "On a class of direction-finding forecasting algorithms", Amir Atiya, Proc. Second International Conference on Neural Networks in the Capital Markets, Pasadena, CA, November 1994.

[64] "On the required size of multilayer networks for implementing real-valued functions", Amir Atiya, Proc. IEEE World Congress on Computational Intelligence, Orlando, FL, June 1994.

[65] "How do initial conditions affect generalization performance of large networks", Chuanyi Ji and Amir Atiya, Neural Networks for Computing, Snowbird, Utah, April 1993 (Abstract only).

[66] "Anticipatory control: a software retrofit for current plant controllers", S. Parthasarathy, A. Parlos, and A. Atiya, Trans. ANS Winter Annual Meeting, November 1993, San Fransisco, CA.

[67] "Unifying recurrent network training algorithms", Amir Atiya and Alexander Parlos, Proc. World Congress on Neural Networks, Portland, OR, July 1993.

[68] "Application of the recurrent multilayer perceptron for transient modeling of complex process systems", A. Parlos, K. Chong, and A. Atiya, Proc. World Congress on Neural Networks, Portland, OR, July 1993.

[69] "Nonlinear system identification using spatio-temporal neural networks", Amir Atiya and Alexander Parlos, Proc. Internat. Joint Neural Network Conf., Baltimore, MD, June 1992.

[70] "Direct adaptive control of process systems using recurrent neural networks", S. Parthasarathy, A. Parlos, and A. Atiya, Proc. Automatic Control Conference ACC, Chicago, IL, July 1992.

[71] "Incipient fault detection in power plants using accelerated neural network algorithms", A. Parlos, M. Jayakumar, and A. Atiya, EPRI 5th Incipient Failure Detection Conf., Knoxville, TN, September 1992.

[72] "Model predictive adaptive control using recurrent neural networks", S. Parthasarathy, A. Parlos, and A. Atiya, Proc. 8th Power Plant Dynamics, Control, and Testing Symposium, Knoxville, TN, May 1992.

[73] "A learning algorithm for spatio-temporal neural networks", Amir Atiya and Alexander Parlos, Neural Networks for Computing, Snowbird, Utah, April 1992 (Abstract only).

[74] "An algorithm for training multilayer perceptron", Amir Atiya, Proc. Internat. Joint Neural Network Conf., Seattle, WA, July 1991 (Abstract only).

[75] "Parameter estimation in space systems using recurrent neural networks", A. Parlos, A. Atiya, and J. Sunkel, Proc. 1991 AIAA Conf. on Guidance, Navigation and Control, August 1991, New Orleans, LA.

[76] "Recurrent multilayer perceptron for nonlinear system identification", A. Parlos, A. Atiya, K. Chong, W. Tsai, and B. Fernandez, Proc. Internat. Joint Neural Network Conf., Seattle, WA, July 1991.

[77] "A hybrid recurrent neural network architecture for learning the dynamics of nonlinear systems", A. Atiya, A. Parlos, K. Chong, and W. Tsai, Neural Networks for Computing, Snowbird, Utah, April 1991 (Abstract only).

[78] "Transient response prediction in nuclear power plants using neural networks", A. Parlos, A. Atiya, K. Chong, W. Tsai, and B. Fernandez, Proc. AI91: Frontiers in Innovative Computing for the Nuclear Industry, September 1991, Jackson, WY.

[79] "Empirical modeling of nuclear power plants using neural networks", A. Parlos, A. Atiya, and K. Chong, Trans. ANS Summer Annual Meeting, June 1991, Orlando, FL.

[80] "Dynamic gradient descent learning algorithms for enhanced empirical modeling of power plants", A. Parlos, A. Atiya, and K. Chong, Trans. ANS Winter Annual Meeting, November 1991, San Fransisco, CA.

[81] "A method for the associative storage of analog vectors", Amir Atiya and Yaser Abu-Mostafa, in Advances in Neural Information Processing Systems NIPS-2, Dave Touretzky, Ed., Morgan Kaufmann, 1990.

[82] "On the set of memory vectors which can be stored in continuous neural nets", Amir Atiya, Neural Networks for Computing, Snowbird, Utah, April 1990 (Abstract only).

[83] "Learning on a general network", Amir Atiya, in Neural Information Processing Systems NIPS, Dana Anderson, Ed., American Institute of Physics, New York, NY 1988.

[84] "A neural unsupervised learning technique", Amir Atiya, Neural Networks: Abstracts of the First Ann. INNS Meeting, September 1988, Boston, MA, (Vol. 1, Suppl. 1).

[85] "Optimal neural spike classification", Amir Atiya and James Bower, in Neural Information Processing Systems NIPS, Dana Anderson, Ed., American Institute of Physics, New York, NY 1988.

[86] "A modified Fisher criterion for feature extraction", Amir Atiya, Proc. IEEE Int. Conf. Systems, Man, Cybernetics, Atlanta, GA, October 1986.

[87] "An assessment of feature extraction methods and their feature vectors", T. El-Sheikh and A. Atiya, Tenth Int. Congr. Stat., Comp. Sc., Social and Demogr. Res., Ain Shams University, Cairo, Egypt, 1985.

[88] "An efficient technique for extracting an effective set of features", T. El-Sheikh and A. Atiya, Seventh IASTED Int. Symp. Robotics and Automation, Lugano, Switzerland, 1985.

[89] "an iterative feature extraction technique", T. El-Sheikh and A. Atiya, IASTED Int. Symp. Appl. Signal Proc. and Digital Filtering, Paris, 1985.