[2] "Forecasting hotel arrivals and occupancy using Monte Carlo simulation", Athanasius Zakhary, Amir Atiya, Hisham El-Shishiny, and Neamat El Gayar, conditionally accepted, Journal of Revenue & Pricing Management, expected 2010.
[3] "Combination of long Term and short term forecasts, with application to tourism demand forecasting", Robert Andrawis, Amir F. Atiya, and Hisham El-Shishiny, conditionally accepted, International Journal of Forecasting, 2009.
[4] "An empirical comparison of machine learning models for time series forecasting", Nesreen K. Ahmed, Amir F. Atiya, Neamat El Gayar, and Hisham El-Shishiny, accepted for publication, to appear in Econometric Reviews, Vol. 29, No. 5-6, 2010.
[5] "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.
[6] "A Penalized Likelihood based Pattern Classification Algorithm", Amir F. Atiya and Ahmed Al-Ani, Pattern Recognition, Volume 42, pp. 2684 – 2694, 2009.
[7] "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.
[8] "An efficient maximum likelihood volatility estimation method for the Heston model", Amir Atiya and Steve Wall, Quantitative Finance, Vol. 9, No. 3, pp. 289–296, April 2009.
[9] "Novel ensemble techniques for regression with missing data", Mostafa Hassan, Amir Atiya, Neamat El Gayar, and Raafat El-Fouly, accepted for publication, New Mathematics and Natural Computation, to appear, 2009.
[10] "Symbolic function network", George Eskander and Amir Atiya, Neural Networks, to appear, 2009.
[11] "Hyperspherical prototypes for pattern classification", Hatem Fayed, Amir Atiya, and Sherif Hashem, International Journal of Pattern Recognition and Artificial Intelligence, to appear, 2009.
[12] "A neural network based dynamic forecasting model for trend impact analysis", Nedaa Agami, Amir Atiya, Mohemed Saleh, and Hisham El-Shishiny, Technological Forecasting & Social Change, Vol. 76, 952–962, 2009.
[13] "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.
[14] "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.
[15] " Self-generating prototypes for pattern classification", Hatem Fayed, Sherif Hashem, and Amir Atiya, Pattern Recognition, Vol. 40, pp. 1498-1509, 2007.
[16] "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.
[17] "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.
[18] "Sparse basis selection: new results and application to adaptive video traffic flow forecasting", Amir F. Atiya, Mohamed Aly, and Alexander G. Parlos, IEEE Transactions on Neural Networks, Vol. 16, No. 5, pp. 1136-1146, September 2005.
[19] "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.
[20] "Estimating the posterior probabilities using the K-nearest neighbor rule", Amir Atiya, Neural Computation, Vol. 17, No. 3, pp. 731-740, March 2005.
[21] "Maximum drawdown", Malik Magdon-Ismail and Amir Atiya, Risk Magazine, October 2004.
[22] "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.
[23] "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.
[24] "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.
[25] "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.
[26] "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.
[27] "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.
[28] "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.
[29] "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.
[30] "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.
[31] "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.
[32] "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.
[33] "The early restart algorithm", Malik Magdon-Ismail and Amir Atiya, Neural Computation, Vol. 12, No. 6, pp. 1303-1312, June 2000.
[34] "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.
[35] "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.
[36] "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.
[37] "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.
[38] "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.
[39] "Introduction to financial forecasting", Yaser Abu-Mostafa and Amir Atiya, Applied Intelligence, Vol. 6, pp. 205-213, 1996.
[40] "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.
[41] "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.
[42] "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.
[43] "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.
[44] "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.
[45] "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.
[46] "An analog feedback associative memory", Amir Atiya and Yaser Abu-Mostafa, IEEE Trans. Neural Networks, Vol. 4, No. 1, pp. 117-126, January 1993.
[47] "Recognition of multiunit neural signals", Amir Atiya, IEEE Trans. Biomedical Engineering, Vol. 39, No. 7, pp. 723-729, July 1992.
[48] "Nonlinear identification of process dynamics using neural networks", A. Parlos, A. Atiya, K. Chong, and W. Tsai, Nuclear Technology, January 1992.
[49] "An unsupervised learning technique for artificial neural networks", Amir Atiya, Neural Networks, Vol. 3, No. 6, pp. 707-711, 1990.
[50] "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.
[51] "Learning without a teacher in neural networks", (in German) Amir Atiya, Design \& Elektronik, March 21, 1989.
[52] "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] "A deterministic annealing approach to learning Bayesian networks", A. Hassan, A. Atiya, and I. Talkhan, Dept Computer Engineering, Cairo University, Tech Report, under submission to a journal.
[2] "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.
[3] "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.
[4] "New hyperspheres for pattern classification", H. Fayed, S. Hashem, and A. Atiya, accepted, to appear in Proceedings 1st International Computer Engineering Conference (ICENCO-2004), Cairo, Egypt, December 2004.
[5] "The Effect of Individual Input Performance and Correlations in the Subset Selection Problem", Amir Atiya, accepted, to appear in Proceedings 1st International Computer Engineering Conference (ICENCO-2004), Cairo, Egypt, December 2004.
[6] "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.
[7] "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.
[8] "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.
[9] "Using high, low, and close data for volatility estimation", Amir Atiya and Malik Magdon-Ismail, Proc 16th IMACS World Congress, Lausanne, Switzerland, August 2000.
[10] "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.
[11] "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.
[12] "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.
[13] "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.
[14] "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).
[15] "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.
[16] "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.
[17] "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.
[18] "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.
[19] "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.
[20] "Trading system design using neural networks", Amir Atiya, Invited Talk, Proceedings Int. Joint Conf. Neural Networks, IJCNN-99, (Abstract only), Washington, DC, July 1999.
[21] "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.
[22] "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.
[23] "A Bayesian approach to estimating mutual fund returns", Amir Atiya and Malik Magdon-Ismail, Proceedings Computational Finance Conf. CF-99, New York, January 1999.
[24] "Neural networks for density estimation", Malik Magdon-Ismail and Amir Atiya, in Proceedings Neural Information Processing Systems Conf NIPS-98, Denver, Colorado, November 1998.
[25] "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.
[26] "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.
[27] "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.
[28] "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.
[29] "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.
[30] "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.
[31] "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.
[32] "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.
[33] "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.
[34] "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.
[35] "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.
[36] "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.
[37] "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.
[38] "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.
[39] "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).
[40] "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.
[41] "Unifying recurrent network training algorithms", Amir Atiya and Alexander Parlos, Proc. World Congress on Neural Networks, Portland, OR, July 1993.
[42] "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.
[43] "Nonlinear system identification using spatio-temporal neural networks", Amir Atiya and Alexander Parlos, Proc. Internat. Joint Neural Network Conf., Baltimore, MD, June 1992.
[44] "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.
[45] "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.
[46] "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.
[47] "A learning algorithm for spatio-temporal neural networks", Amir Atiya and Alexander Parlos, Neural Networks for Computing, Snowbird, Utah, April 1992 (Abstract only).
[48] "An algorithm for training multilayer perceptron", Amir Atiya, Proc. Internat. Joint Neural Network Conf., Seattle, WA, July 1991 (Abstract only).
[49] "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.
[50] "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.
[51] "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).
[52] "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.
[53] "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.
[54] "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.
[55] "Review of the book: Introduction to Random Processes, by W. Gardner, McGraw-Hill, 1986", Amir Atiya, IEEE Communications Magazine, November 1991.
[56] "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.
[57] "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).
[58] "Learning on a general network", Amir Atiya, in Neural Information Processing Systems NIPS, Dana Anderson, Ed., American Institute of Physics, New York, NY 1988.
[59] "A neural unsupervised learning technique", Amir Atiya, Neural Networks: Abstracts of the First Ann. INNS Meeting, September 1988, Boston, MA, (Vol. 1, Suppl. 1).
[60] "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.
[61] "A modified Fisher criterion for feature extraction", Amir Atiya, Proc. IEEE Int. Conf. Systems, Man, Cybernetics, Atlanta, GA, October 1986.
[62] "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.
[63] "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.
[64] "an iterative feature extraction technique", T. El-Sheikh and A. Atiya, IASTED Int. Symp. Appl. Signal Proc. and Digital Filtering, Paris, 1985.