Publications

Book

H.T. Siegelmann
Neural Networks and Analog Computation:
Beyond the Turing Limit, Birkhauser
Boston, December 1998


More informations here
 Hava's Book Cover Picture


Theses
  • Ph.D. Thesis: "Foundation of Recurrent Neural Networks," Rutgers University, 1993
  • Master Thesis: "Document Allocation in Multiprocessor Information Retrieval Systems: An Application of Genetic Algorithms," The Hebrew University, 1992


Refereed Papers in Professional Journals
  1. F. Roth, H.T. Siegelmann and R. J. Douglas, "The Self-Construction and -Repair of a Foraging Organism by Explicitly Specified Development from a Single Cell" Artificial Life, to appear
  2. S. Sivan, O. Filo and H. Siegelman, "Application of Expert Networks for Predicting Proteins Secondary Structure," Biomolecular Engineering, Volume 24, Issue 2, June 2007, 237-243
  3. W. Bush and H.T. Siegelmann,"Circadian Synchrony in Networks of Protein Rhythm Driven Neurons" Complexity Volume 12, Issue 1 (September/October 2006) 67-72
  4. T. Leise and H Siegelmann, "Dynamics of a multistage circadian system," Journal of Biological Rhythms, August, 21:4 (2006), 314-323 :: Media Attention in various journals and news in the USA and other countries: e.g. Boston Globes, Yahoo!News, Forbes, United Press International, National Public Radio, Medical breakthroughs, Science Daily, Good morning New York, etc.
  5. L. Glass, T. J. Perkins, J. Mason, H. T. Siegelmann and R. Edwards, "Chaotic Dynamics in an Electronic Model of a Genetic Network ," Journal of Statistical Physics Volume 121 Numbers 5-6: 969-994. 2006
  6. Loureiro, O. and Siegelmann, H., "Introducing an Active Cluster-Based Information Retrieval Paradigm," Journal of the American Society for Information Science and Technology, vl 56, n. 10, August 2005, pp. 1024-1030
  7. A. Roitershtein, A. Ben-Hur and H.T. Siegelmann "On probabilistic analog automata," Theoretical Computer Science, 320(2-3) pp. 449-464, June 2004
  8. A. Ben-Hur, H.T. Siegelmann, "Computing with Gene Networks," Chaos: An Interdisciplinary Journal of Nonlinear Science, 14(1) pp. 145-151, March 2004 (Work was chosen as the work to describe in physics news)
  9. A. Ben-Hur, J. Feinberg, S. Fishman and H. T. Siegelmann "Random matrix theory for the analysis of the performance of an analog computer: a scaling theory," Phys. Lett. A. 323(3-4) pp. 204-209, March 2004
  10. A. Ben-Hur, J. Feinberg, S. Fishman and H. T. Siegelmann, "Probabilistic analysis of a differential equation for linear programming," Journal of Complexity, 19(4) pp. 474-510 August 2003
  11. J. P. Neto, H. T. Siegelmann, and J. F. Costa. "Symbolic processing in neural networks," Journal of the Brazilian Computer Society, 8(3), July 2003
  12. S. Eldar, H. T. Siegelmann, D. Buzaglo, I. Matter, A. Cohen, E. Sabo, J. Abrahamson, "Conversion of Laparoscopic Cholecystectomy to open cholecystectomy in acute cholecystitis: Artificial neural networks improve the prediction of conversion," World Journal of Surgery. 2002 Jan 26(1): 79-85
  13. A. Ben-Hur, H.T. Siegelmann and S. Fishman. "A theory of complexity for continuous time dynamics." Journal of Complexity 18(1) : 51-86, 2002
  14. H.T. Siegelmann, "Neural and Super-Turing Computing," Philosophy 2002
  15. A. Ben-Hur, D. Horn, H.T. Siegelmann and V. Vapnik, "Support vector clustering," Journal of Machine Learning Research 2:125-137, 2001
  16. Hava T. Siegelmann: Neural Computing. Bulletin of the EATCS 73: 107-130 (2001)
  17. H.T. Siegelmann A., Ben-Hur, S. Fishman, "Comments on Attractor Computing," in International Journal of Computing Anticipatory Systems, D.M. Dubois, ed. 2001
  18. R. Edwards, H.T. Siegelmann, K. Aziza and L. Glass, "Symbolic dynamics and computation in model gene networks", Chaos 11(1): 160-169, 2001
  19. H. Lipson and H.T. Siegelmann, "Clustering Irregular Shapes Using High-Order Neuron," Neural Computation 12(10), August 2000: 2331-2353
  20. D. Lange, H.T. Siegelmann, H. Pratt, and G.F. Inbar, "Overcoming Selective Ensemble Averaging: Unsupervised Identification of Event Related Brain Potentials." IEEE Transactions on Biomedical Engineering, 47(6), June 2000: 822-826
  21. H. Karniely and H.T. Siegelmann, "Sensor Registration Using Neural Networks," IEEE transactions on Aerospace and Electronic Systems, 36(1), 2000: 85-98
  22. H.T. Siegelmann, "Stochastic Analog Networks and Computational Complexity," Journal of Complexity, 15(4), 1999: 451-475
  23. H.T. Siegelmann, A. Ben-Hur and S. Fishman, "Computational Complexity for Continuous Time Dynamics," Physical Review Letters, 83(7), 1999: 1463-1466
  24. H.T. Siegelmann and M. Margenstern, "Nine Neurons Suffice for Turing Universality," Neural Networks, 12, 1999: 593-600
  25. R. Gavaldà and H.T. Siegelmann, "Discontinuities in Recurrent Neural Networks," Neural Computation, 11(3), April 1999: 715-745
  26. H.T. Siegelmann and S. Fishman, "Computation by Dynamical Systems," Physica D 120, 1998: 214-235
  27. A. Galperin, Y. Kimhi, E. Nissan, and H.T. Siegelmann, "FULECON's Heuristics, their Rationale, and their Representations," The New Review of Applied Expert Systems 4, 1998: 163-176
  28. Joachim Utans, John Moody, Steve Rehfuss, and Hava Siegelmann, "Selecting Input Variables via Sensitivity Analysis: Application to Predicting the U.S. Business Cycle," Proceedings of Computational Intelligence in Financial Engineering, IEEE Press, 1995
  29. H.T. Siegelmann, E. Nissan, and A. Galperin, "A Novel Neural/Symbolic Hybrid Approach to Heuristically Optimized Fuel Allocation and Automated Revision of heuristics in Nuclear Engineering," Advances in Engineering Software, 28(9), 1997: 581-592
  30. J.L. Balcázar, R. Gavaldà, and H.T. Siegelmann, "Computational Power of Neural Networks: A Characterization in Terms of Kholmogorov Complexity," IEEE Transactions on Information Theory, 43(4), July 1997: 1175-1183
  31. H.T. Siegelmann, B.G. Horne, and C.L.Giles, "Computational Capabilities of Recurrent NARX Neural Networks," IEEE Transaction on Systems, Man and Cybernetics-part B: Cybernetics, 27(2), 1997: 208-215
  32. E. Nissan, H.T. Siegelmann, A. Galperin, and S. Kimhi, "Upgrading Automation for Nuclear Fuel In-Core Management: From the Symbolic Generation of Configurations, to the Neural Adaptation of Heuristics," Engineering with Computers, 13(1), 1997: 1-19
  33. O. Frieder and H.T. Siegelmann, " Document Allocation: A Genetic Algorithm Approach," IEEE Transactions on Knowledge and Data Engineering, 9(4), 1997: 640-642
  34. H.T. Siegelmann and C.L. Giles, "The Complexity of Language Recognition by Neural Networks," Journal of Neurocomputing; Special Issue "Recurrent Networks for Sequence Processing," Editors: M. Gori, M. Mozer, A.H. Tsoi, W. Watrous, 15(3-4), 1997: 327-345
  35. H.T. Siegelmann, "On NIL: The Software Constructor of Neural Networks," Parallel Processing Letters, 6(4), 1996: 575-582
  36. H.T. Siegelmann, "The Simple Dynamics of Super Turing Theories," Theoretical Computer Science, 168(2)(special issue on UMC), 1996: 461-472
  37. H.T. Siegelmann, "Recurrent Neural Networks and Finite Automata," Journal of Computational Intelligence, 12(4), 1996: 567-574
  38. J. Kilian and H.T. Siegelmann, "The Dynamic Universality of Sigmoidal Neural Networks," Information and Computation, 128(1), 1996: 45-56
  39. H.T. Siegelmann, "Analog Computational Power," Science, 271(19), January 1996: 373
  40. B. DasGupta, H.T. Siegelmann and E. Sontag, "On the Complexity of Training Neural Networks with Continuous Activation Functions," IEEE Transactions on Neural Networks, 6(6), 1995: 1490-1504
  41. H.T. Siegelmann, "Computation Beyond the Turing Limit," Science, 238(28), April 1995: 632-637
  42. H.T. Siegelmann and E.D. Sontag, "Computational Power of Neural Networks," Journal of Computer System Sciences, 50(1), 1995: 132-150
  43. H.T. Siegelmann and E.D. Sontag, "Analog Computation via Neural Networks," Theoretical Computer Science, 131, 1994: 331-360
  44. H.T. Siegelmann and E.D. Sontag, "Turing Computability with Neural Networks," Applied Mathematics Letters, 4(6), 1991: 77-80


Book Chapters
  1. Bhaskar DasGupta, Derong Liu and Hava Siegelmann, Neural Networks, Handbook on Approximation Algorithms and Metaheuristics, Teofilo F. Gonzalez (editor), Chapman & Hall/CRC (Computer & Information Science Series, series editor: Sartaj Sahni). pp. 22.1-22.14, 2007
  2. H. T. Siegelmann, "Neural Computing". New Trends in Computer Science, Gheroge Paul editor, 2003
  3. H.T. Siegelmann, "Neural Automata and Computational Complexity," in Handbook of Brain Theory and Neural Networks, Michael A. Arbib (ed.), 2002
  4. H.T. Siegelmann, "Universal Computation and Super-Turing Capabilities," in Field Guide to Dynamical Recurrent Networks, S.C. Kremer and J.F. Kolen (eds.), IEEE Press, 2000
  5. H.T. Siegelmann, "Finite vs. Infinite Descriptive Length in Neural Networks and the Associated Computational Complexity," in Finite vs. Infinite: Contributions to an Eternal Dilemma, C. Calude and Gh. Paun (eds.), Springer Verlag, 2000
  6. H.T. Siegelmann, "Neural Automata and Computational Complexity," in Handbook of Brain Theory and Neural Networks, Michael A. Arbin (ed.), 2000
  7. H. Lipson and H.T. Siegelmann, "High Order Eigentensors as Symbolic Rules in Competitive Learning," in Hybrid Neural Symbolic Integration, S. Wermter and R. Sun (eds.), Springer, 1999
  8. H.T. Siegelmann, "Neural Dynamics with Stochasticity," in Adaptive Processing of Sequences and Data Structures, C.L. Giles and M. Gori (eds.), Springer, 1998: 346-369
  9. H.T. Siegelmann, "Computability with Neural Networks," in Lectures in Applied Mathematics, Vol. 32, J. Reneger, M. Shub, and S. Smale (eds.), American Mathematical Society, 1996: 733-747
  10. H.T. Siegelmann, "Neural Automata," in Shape, Structures and Pattern Recognition, D. Dori and F. Bruckstein (eds.), World Scientific, 1995
  11. H.T. Siegelmann, "Towards a Neural Programming Language," in Shape, Structures and Pattern Recognition, D. Dori and F. Bruckstein (eds.), World Scientific, 1995
  12. H.T. Siegelmann, "Recurrent Neural Networks," in The 1000th Volume of Lecture Notes in Computer Science: Computer Science Today, Jan Van Leeuwen (ed.), Springer Verlag, 1995: 29-45
  13. H.T. Siegelmann, "Welcoming the Super-Turing theories," in Lecture Notes in Computer Science, Vol. 1012, M. Bartosek, J. Staudek, J. Wiedermann (eds.), Springer Verlag, 1995: 83-94
  14. H.T. Siegelmann, B.G. Horne, and C.L. Giles, "What NARX Networks Can Compute," in Lecture Notes in Computer Science: Theory and Practice of Informatics, Vol. 1012, M. Bartosek, J. Staudek, J. Wiedermann (eds.), Springer Verlag, 1995: 95-102
  15. B. DasGupta, H.T. Siegelmann, and E. Sontag, "On the Intractability of Loading Neural Networks," in Theoretical Advances in Neural Computation and Learning,
  16. V.P. Roychowdhury, K.Y. Siu, and A. Orlitsky (eds.), Kluwer Academic Publishers, 1994: 357-389
  17. H.T. Siegelmann, "On the Computational Power of Probabilistic and Faulty Neural Networks," in Lecture Notes in Computer Science, Vol. 820: Automata, Languages and Programming, S. Abiteboul and E. Shamir (eds.), Springer Verlag, 1994: 20-34
  18. H.T. Siegelmann and O. Frieder, "Document Allocation in Multiprocessor Information Retrieval Systems," in Lecture Notes in Computer Science, Vol. 759: Advanced Database Concepts and Research Issues, N.R. Adam and B. Bhargava (eds.), Springer Verlag, November 1993: 289-310


In Conferences
  1. M. Olsen and H. Siegelmann, Multi-Agent System that Attains Longevity via Death. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI). Jan 2007
  2. L. Holtzman and H. Siegelmann "Iput Driven Dynamic Attractors", Computational and Systems Neuroscience, Salt Lake City, February 2007
  3. L. Holtzman and H. Siegelmann "Exact Neural Bayesian Learning and Inference over Graphical Models", Computational and Systems Neuroscience Salt Lake City, February 2007
  4. M. Olsen and H. Siegelmann, Artificial Death for Attaining System Longevity. Proceedings of the 50th Anniversary Summit of Artificial Intelligence Summit. Switzerland, pp. 217-218. July 2006
  5. Kyle Harrington and Hava Siegelmann, "Adaptive Multi-Modal Sensors" Proceedings of the 50th Anniversary Summit of Artificial Intelligence Summit. Switzerland
  6. Will Bush and Hava Siegelmann "Genetic based neurons" Computational Neural systems, Salt Lake City, 2005
  7. Guo AnYuan and Hava Siegelmann, "Time-Warped Longest Common Subsequence Algorithm for Music Retrieval," International Conference on Music Information Retrieval (ISMIR'04), October, Spain
  8. Eric Bittman, Yossi Chait, C.V. Hollot, M. Harrington and H. Siegelmann, "Is the Mammalian Circadian Clock a Resonant-Circuit Oscillator?", Society for Research on Biological Rhythms, Whistler, BC, 2004
  9. Yanhong Tong and Hava Sieglemann "Simulation mammalian molecular circadian oscillators by dynamic gene network" Eighth Annual International Conference on Research in Computational Molecular Biology, March 2004
  10. Shaolei Lu, AnYuan Guo, Klaus Becker, Hava Siegelmann, Paola Sebastiani, Kyle MacBeth, Joseph Jerry , "Microarray Analysis of Global Gene Expression in the Mammary Gland Following Estrogen and Progesterone Treatment of Ovariectomized Mice," Second Annual AACR International Conference on Frontiers in Cancer Prevention Research, Phoenix, Arizona, October 2003
  11. T. Jaakkola and H. Siegelmann. "Active information retrieval." Advances in Neural Information processing systems 14, 2001
  12. Pedro Rodrigues, Jose Felix Costa, Hava T. Siegelmann: Verifying Properties of Neural Networks. IWANN (1) 2001: 158-165
  13. Asa Ben-Hur, Hava T. Siegelmann, "Computation in Gene Networks," MCU 2001: 11-24
  14. A. Ben-Hur and H.T. Siegelmann, Computation in gene networks. in: M. Margenstern and Y. Rogozhin (Eds.): MCU 2001, LNCS 2055, pp. 11-24, 2001
  15. D. Horn, I. Opher, M. Epstein and H. T. Siegelmann. "Clustering of Documents using Latent Semantic Analysis" Proceedings of the DAS2000, Rio-December 2000
  16. A. Ben-Hur, D. Horn, H.T. Siegelmann and V. Vapnik, "A Support Vector Method for Hierarchical Clustering" Fourteenth Annual Conference on Neural Information Processing Systems, Denver, Colorado, November 2000
  17. A. Ben-Hur, D. Horn, H.T. Siegelmann and V. Vapnik. "A Support Vector Clustering Method" Proceedings of the 15th International Conference on Pattern Recognition (ICPR), 728-731, 2000, Barcelona
  18. H.T. Siegelmann and A. Roitershtein, "Noisy Neural Computation," Proceedings of Thirteenth Annual Conference on Neural Information Processing Systems, Denver, Colorado, 30 November-2 December, 1999
  19. H.T. Siegelmann, A. Ben-Hur, and S. Fishman, "Computational Complexity for Continuous Time Dynamics," Proceedings of Third International Conference on Computing Anticipatory Systems (CASYS'99), Liege, Belgium, 9-14 August, 1999
  20. Hod Lipson, Hava T. Siegelmann: High Order Eigentensors as Symbolic Rules in Competitive Learning. Hybrid Neural Systems 1998: 286-297
  21. H.T. Siegelmann and S. Fishman, 'Attractor Systems and Analog Computation," Proceedings of the Second International Conference on Knowledge-Based Intelligent Electronic Systems (KES'98), Adelaide, Australia, 21-23 April, 1998
  22. H. Lipson, Y. Hod, and H.T. Siegelmann, "High-Order Clustering Metrics for Competitive Learning Neural Networks," Proceedings of the Israel-Korea Bi-National Conference on New Themes in Computer Aided Geometric Modeling, Tel-Aviv, Israel, February 18-19, 1998
  23. J.P. Neto, H.T. Siegelmann, and J.F. Costa, "Turing Universality of neural Nets Revisited," Proceedings of the Sixth International Conference on Computer Aided Systems Technology (EUROCAST'97). In Franz Pichler and Roberto Moreno-Diaz (eds.), Lecture Notes in Computer Science (LNCS) 1333, 1997: 3651-366
  24. D.H. Lange, H.T. Siegelmann, H. Pratt, and G.F. Inbar, "A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network Structure," Proceedings of the International Conference on Neural Information Proceeding (NIPS), Denver, Colorado, December 1997
  25. Y. Finkelstein and H.T. Siegelmann, "A Stochastic Model to Study Degenerative Disorders in the Central Nervous System," The Israel Neurological Association Annual Meeting, Zichron-Yaakov, November 1997
  26. H.T. Siegelmann and S. Fishman, "Computation in Dynamical Systems," Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, October 1997
  27. H.T. Siegelmann, A. Ofri, and H. Guterman, "Applying Modular Networks and Fuzzy Logic Controllers to Nonlinear flexible Structures," Proceedings of the IEEE International Conference on Fuzzy Logic, September 1997
  28. J.P. Neto, H.T. Siegelmann, and J.F. Costa, "Implementation of Programming Languages with Neural Nets," Proceedings of the First International Conference on Computing Anticipatory Systems (CASYS'97), HEC, Liege, Belgium, August 1997
  29. G. Arieli and H.T. Siegelmann, "ANN Approach vs. the Symbolic Approach in AI," Proceedings of the Thirteenth Israeli Conference on Artificial Intelligence and Computer Vision (IAICV'97), Tel-Aviv, February 1997
  30. H.T. Siegelmann, 'Recurrent Neural Networks," AMS Proceedings, Park-City, 8/1995
  31. Hava T. Siegelmann: Welcoming the Super Turing Theories. SOFSEM 1995: 83-94
  32. Bill G. Horne, Hava T. Siegelmann, C. Lee Giles: What NARX Networks Can Compute. SOFSEM 1995: 95-102
  33. H.T. Siegelmann, "Recurrent Neural Networks and Finite Automata," Proceedings of the Twelfth International Conference on Pattern Recognition , October 1994, Jerusalem
  34. E. Nissan, H.T. Siegelmann, and A. Galperin, "An Integrated Symbolic and Neural Network Architecture for Machine Learning in the domain of Nuclear Engineering," Proceedings of the Twelfth International Conference on Pattern Recognition, October 1994, Jerusalem
  35. E. Nissan, H.T. Siegelmann, A. Galperin, and S. Kimhi, "Towards Full Atomization of the Discovery of Heuristics in a Nuclear Engineering Project: Integration with a Neural Information Language," Proceedings of the Eight International Symposium on Methodologies for Intelligent Systems, October 1994, Charlotte, North Carolina
  36. H.T. Siegelmann, "Neural Programming Language," Proceedings of the Twelfth National Conference on Artificial Intelligence, AAAI-94, July 31-August 4, 1994, Seattle, Washington. Menlo PARK (CA): AAAI Press/The MIT Press, 1994, Vol. 2: 877-882
  37. B. DasGupta, H.T. Siegelmann, and E. Sontag, "On a Learnability Question Associated to Neural Networks with Continuous Activations," Proceedings of the Sixth ACM Workshop on Computational Learning (COLT), New Brunswick NJ, July 1994
  38. H.T. Siegelmann, "On the Computational Power of Probabilistic and Faulty Neural Networks," Proceedings of the International Colloquium on Automata, Languages, and Programming (ICALP), July 1994
  39. J. Kilian and H.T. Siegelmann, "Computability with the Classical Sigmoid," Proceedings of the Fifth ACM Workshop on Computational Learning (COLT), Santa Cruz, July 1993: 137-143
  40. Hava T. Siegelmann, Ophir Frieder: Document Allocation In Multiprocessor Information Retrieval Systems. Advanced Database Systems 1993: 289-310
  41. H.T. Siegelmann and E.D. Sontag, "Analog Computation via Neural Networks," Proceedings of the Second Israel Symposium on Theory of Computing and Systems (ISTCS), Natanya, Israel, June 1993: 98-107
  42. J.L. Balcázar, R. Gavalda, JH.T. Siegelmann, and E.D. Sontag, "Some Structural Complexity Aspects of Neural Computation," Proceedings of the IEEE Conference on Structure in Complexity Theory, San Diego, California, May 1993: 253-265
  43. H.T. Siegelmann and E.D. Sontag, "Some Recent Results on Computing with 'Neural Nets'," Proceedings of the IEEE Conference on Decision and Control, Tucson, Arizona, December 1992: 1476-1481
  44. H.T. Siegelmann and E.D. Sontag, "On the Computational Power of Neural Networks," Proceedings of the Fifth ACM Workshop on Computational Learning Theory (COLT), Pittsburgh, Penn., July 1992: 440-449
  45. H.T. Siegelmann, E.D. Sontag, and C.L. Giles, "The Complexity of Language Recognition by Neural Networks," Algorithms, Software, Architecture (J. van Leuwen, ed.), North Holland, Amsterdam, 1992: 329-335. (Proceedings of the Twelfth IFIP World Computer Congress)
  46. H.T. Siegelmann and O. Frieder, "The Allocation of Documents in Multiprocessor Information Retrieval Systems: An Application of Genetic Algorithms," Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, Charlottesville, Virginia, October 1991
  47. O. Frieder and H.T. Siegelmann, "On the Allocation of Documents in Information Retrieval Systems," Proceedings of the ACM Fourteenth Conference on Information Retrieval (SIGIR), Chicago, Illinois, October 1991
  48. H.T. Siegelmann and B.R. Badrinath, "Integrating Implicit Answers with Object-Oriented Queries," Proceedings of the Conference on Very Large Data Bases, Barcelona, Spain, September 1991





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