Full Publication List of Abu-Mostafa

  1. Complexity of information extraction. Y. Abu-Mostafa. Ph.D. dissertation, California Institute of Technology, May 23, 1983. [Caltech ETD]
  2. A differentiation test for absolute convergence. Y. Abu-Mostafa. Mathematics Magazine, 57(4):228-231, September 1984.
  3. Recognitive aspects of moment invariants. Y. Abu-Mostafa and D. Psaltis. IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-6(6):698-706, November 1984.
  4. Image normalization by complex moments. Y. Abu-Mostafa and D. Psaltis. IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-7(1):46-55, January 1985.
  5. Information capacity of the Hopfield model. Y. Abu-Mostafa and J. St. Jacques. IEEE Trans. on Information Theory, IT-31(4):461-464, July 1985. Reprinted in V. Vemuri (ed.), Artificial Neural Networks: Theoretical Concepts, pp. 96-99, Computer Society Press, 1988. [IEEE]
  6. The complexity of information extraction. Y. Abu-Mostafa. IEEE Trans. on Information Theory, IT-32(4):513-525, July 1986. [IEEE]
  7. Neural networks for computing? Y. Abu-Mostafa. In J. Denker (ed.), Neural Networks for Computing, pp. 1-6, American Institute of Physics, 1986. [ACM]
  8. Optical neural computers (invited). Y. Abu-Mostafa and D. Psaltis. Scientific American 256(3):88-95, March 1987.
  9. Essential average mutual information. Y. Abu-Mostafa. In T. Cover and B. Gopinath (eds.), Open Problems in Communication and Computation, pp. 75-76, Springer-Verlag, 1987
  10. Pointwise universality of the normal form. Y. Abu-Mostafa. In T. Cover and B. Gopinath (eds.), Open Problems in Communication and Computation, pp. 77-83, Springer-Verlag, 1987
  11. On the time-bandwidth proof in VLSI complexity. Y. Abu-Mostafa. IEEE Trans. on Computers, C-36(2):239-240, February 1987.
  12. The capacity of multilevel threshold functions. S. `Olafsson and Y. Abu-Mostafa. IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-10(2):277-281, March 1988. [IEEE]
  13. Lower bound for connectivity in local-learning neural networks. Y. Abu-Mostafa. Journal of Complexity, 4(3):246-255, September 1988. [J. Complexity]
  14. Connectivity versus entropy. Y. Abu-Mostafa. In D. Anderson (ed.), Neural Information Processing Systems (NIPS'87), pp. 1-8, American Institute of Physics, 1988. PS.GZ
  15. Y. Abu-Mostafa (ed.), Complexity in Information Theory, Springer-Verlag, 1988.
  16. Complexity of random problems. Y. Abu-Mostafa. In Y. Abu-Mostafa (ed.), Complexity in Information Theory, pp. 115-131, Springer-Verlag, 1988.
  17. Complexity in neural systems. Y. Abu-Mostafa. In C. Mead (ed.), Analog VLSI and Neural Systems, pp. 353-358, Addison-Wesley, 1988.
  18. Random problems (invited). Y. Abu-Mostafa. Journal of Complexity, 4(4):277-284, December 1988. [J. Complexity]
  19. On the K-winners-take-all network. E. Majani, R. Erlanson, and Y. Abu-Mostafa. In D. Touretzky (ed.), Advances in Neural Information Processing Systems 1 (NIPS'88), pp. 634-642, Morgan Kaufmann, 1989. PS.GZ
  20. The Vapnik-Chervonenkis dimension: Information versus complexity in learning (invited). Y. Abu-Mostafa. Neural Computation, 1:312-317, September 1989.
  21. Information theory, complexity, and neural networks (invited). Y. Abu-Mostafa. IEEE Communications Magazine, 27(11):25-28,81, November 1989. [IEEE]
  22. Neural networks. Y. Abu-Mostafa and D. Schweizer. In R. Suaya and G. Birtwistle (eds.), VLSI and Parallel Computation, pp. 390-415, Morgan Kaufmann, 1990. [ACM]
  23. Learning from hints in neural networks (invited). Y. Abu-Mostafa. Journal of Complexity, 6(2):192-198, June 1990. [J. Complexity]
  24. A method for the associative storage of analog vectors. A. Atiya and Y. Abu-Mostafa. In D. Touretzky (ed.), Advances in Neural Information Processing Systems 2 (NIPS'89), pp. 590-595, Morgan Kaufmann, 1990. PS.GZ
  25. Analog neural networks as decoders. R. Erlanson and Y. Abu-Mostafa. In R. Lippman et al (eds.), Advances in Neural Information Processing Systems 3 (NIPS'90), pp. 585-588, Morgan Kaufmann, 1991. PS.GZ
  26. Neural networks and learning. Y. Abu-Mostafa. In K. Ismail, T. Ikoma, and H. Smith (eds.), Quantum Effect Physics, Electronics and Applications, pp. 7-12, Institute of Physics Publishing, 1992.
  27. An analog feedback associative memory. A. Atiya and Y. Abu-Mostafa. IEEE Trans. on Neural Networks, 4(1):117-126, January 1993. [IEEE]
  28. Hints and the VC dimension. Y. Abu-Mostafa. Neural Computation, 5(2):278-288, March 1993. [ACM]
  29. Learning from hints (invited). Y. Abu-Mostafa. Journal of Complexity, 10(1):165-178, March 1994. [J. Complexity]
  30. A method for learning from hints. Y. Abu-Mostafa. In S. Hanson et al (eds.), Advances in Neural Information Processing Systems 5 (NIPS'92), pp. 73-80, Morgan Kaufmann, 1993. PS.GZ
  31. Financial applications of learning from hints (invited). Y. Abu-Mostafa. In Advances in Neural Information Processing Systems 7 (NIPS'94), pp. 411-418, MIT Press, 1995. PS.GZ
  32. Financial market applications of learning from hints. Y. Abu-Mostafa. In A.-P. Refenes (Ed.), Neural Networks in the Capital Markets, Chapter 15, pp. 221-232. 1995.
  33. Machines that learn from hints. Y. Abu-Mostafa. Scientific American, 272(4):64-69, April 1995. [SciAm]
  34. Hints. Y. Abu-Mostafa. Neural Computation, 7(4):639-671, MIT Press, July 1995. draft PS [NC]
  35. A. Refenes, Y. Abu-Mostafa, J. Moody, and A. Weigend (eds.), Neural Networks in Financial Engineering, World Scientific, 1996.
  36. Introduction to financial forecasting. Y. Abu-Mostafa and A. Atiya. Applied Intelligence, 6(3):205-213, Kluwer Academic Publishers, July 1996.
  37. Monotonicity hints for credit screening. J. Sill and Y. Abu-Mostafa In Proceedings of the International Conference on Neural Information Processing (ICONIP'96), pp. 123-127, Hong Kong, 1996. PS
  38. Bin model for neural networks. Y. Abu-Mostafa and X. Song. In Proceedings of the International Conference on Neural Information Processing (ICONIP'96), pp. 169-173, Hong Kong, 1996. PS
  39. Systematic underprediction of volatility in maximum likelihood methods. M. Magdon-Ismail and Y. Abu-Mostafa. In A. Weigend, Y. Abu-Mostafa, and A-P. N. Refenes (eds.), Decision Technologies for Financial Engineering (NNCM'96), pp. 125-137, World Scientific, Jan. 1997. PS
  40. A. Weigend, Y. Abu-Mostafa, and A.-P. Refenes (eds.), Decision Technologies for Financial Engineering (NNCM'96), World Scientific, 1997. [contents]
  41. Monotonicity Hints. J. Sill and Y. Abu-Mostafa. In Advances in Neural Information Processing Systems 9 (NIPS'96), pp. 634-640, MIT Press, 1997. PS.GZ
  42. Monotonicity: theory and implementation. J. Sill and Y. Abu-Mostafa. In D. DoCampo, A.R. Figueiras-Vidal, and F. Pérez-González (eds.), Intelligent Methods in Signal Processing and Communications, pp. 129-146, Birkhauser, 1997. draft PS [ACM]
  43. Incorporating contextual information in white blood cell identification. X. Song, Y. Abu-Mostafa, J. Sill, and H. Kasdan. In Advances in Neural Information Processing Systems 10 (NIPS'97), pp. 950-956, MIT Press, 1998. PS.GZ
  44. Financial markets: Very noisy information processing (invited). M. Magdon-Ismail, A. Nicholson, and Y. Abu-Mostafa. Proceedings of the IEEE, 86(11):2184-2195, November 1998. [IEEE]
  45. Validation of volatility models. M. Magdon-Ismail and Y. Abu-Mostafa, Journal of Forecasting, 17(5-6):349-368, 1998. draft PS [J. Forecasting]
  46. Estimating model limitation in financial markets. M. Magdon-Ismail, A. Nicholson, and Y. Abu-Mostafa. In L. Xu, et al. (eds.), Intelligent Data Engineering and Learning (IDEAL'98), pp. 19-26, Hong Kong, 1998. PS
  47. No free lunch for early stopping. Z. Cataltepe, Y. Abu-Mostafa, and M. Magdon-Ismail. Neural Computation, 11(4):995-1009, MIT Press, May 1999. [NC]
  48. Image recognition in context: Application to microscopic urinalysis. X. Song, J. Sill, Y. Abu-Mostafa, and H. Kasdan. In Advances in Neural Information Processing Systems 12 (NIPS'99), pp. 963-969, MIT Press, 2000. PS.GZ
  49. Y. Abu-Mostafa, B. LeBaron, A. Lo, and A. Weigend (eds.), Computational Finance 1999, MIT Press, 2000. [review] [archived conf web] [review]
  50. Maximal codeword lengths in Huffman codes. Y. Abu-Mostafa and R. McEliece. Computers and Mathematics with Applications, 39(11):129-134, 2000. Also JPL TDA Progress Report 42-110:188-193, 1992. [JPL] [CMA]
  51. Learning in the presence of noise. M. Magdon-Ismail, A. Nicholson, and Y. Abu-Mostafa. In S. Haykin and B. Kosko (eds.), Intelligent Signal Processing, chapter 3, pp. 108-126, IEEE Press, 2001. draft PS
  52. Minimizing memory loss in learning a new environment. K. Al-Mashouq, Y. Abu-Mostafa, K. Al-Ghoneim. Neurocomputing, 38-40: 1051-1057, 2001. [Neurocomputing]
  53. Financial model calibration using consistency hints. Y. Abu-Mostafa. IEEE Trans. on Neural Networks, 12(4):791-808, July 2001. draft PS.GZ [IEEE]
  54. Robust image recognition by fusion of contextual information. X. Song, Y. Abu-Mostafa, J. Sill, H. Kasdan, and M. Pavel. Information Fusion, 3(4):277-287, 2002. IF
  55. Emergent specialization in swarm systems. L. Li, A. Martinoli, and Y. Abu-Mostafa. In H. Yin, et al. (eds.), Intelligent Data Engineering and Automated Learning -- IDEAL 2002, vol. 2412 of Lecture Notes in Computer Science, pp. 261-266. Springer-Verlag, 2002. [Springer]
  56. The multilevel classification problem and a monotonicity hint. M. Magdon-Ismail, H.-C. Chen, Y. Abu-Mostafa. In H. Yin, et al. (eds.), Intelligent Data Engineering and Automated Learning -- IDEAL 2002, vol. 2412 of Lecture Notes in Computer Science, pp. 410-415. Springer-Verlag, 2002. [Springer]
  57. The maximum drawdown of the Brownian motion. M. Magdon-Ismail, A. Atiya, A. Pratap, and Y. Abu-Mostafa. In Proceedings IEEE Conference on Computational Intelligence in Financial Engineering (CIFEr'03), pp. 243-247, Hong Kong, March 2003
  58. CGBoost: Conjugate Gradient in Function Space. L. Li, Y. Abu-Mostafa, and A. Pratap. Computer Science Technical Report CaltechCSTR:2003.007, California Institute of Technology, Aug. 2003. [CSTR]
  59. Diversity and Specialization in Collaborative Swarm Systems. L. Li, A. Martinoli, and Y. Abu-Mostafa. In C. Anderson and T. Balch (eds.), Proceedings of the 2nd International Workshop on the Mathematics and Algorithms of Social Insects, pp. 91-98, Atlanta, GA, 2003.
  60. On the maximum drawdown of a Brownian motion. M. Magdon-Ismail, A. Atiya, A. Pratap, and Y. Abu-Mostafa. Journal of Applied Probability, 41(1):147-161, March 2004. draft PDF [Applied Prob]
  61. The Bin Model. Y. Abu-Mostafa, X. Song, A. Nicholson, and M. Magdon-Ismail. Computer Science Technical Report CaltechCSTR:2004.002, California Institute of Technology, July 2004. [CSTR]
  62. Learning and Measuring Specialization in Collaborative Swarm Systems. L. Li, A. Martinoli, and Y. Abu-Mostafa. Adaptive Behavior, 12(3-4):199-212, 2004. [PS.GZ] [Adaptive Behavior]
  63. Pruning Training Sets for Learning of Object Categories. A. Angelova, Y. Abu-Mostafa, and P. Perona. In Computer Vision and Pattern Recognition, 2005 (CVPR'05). Vol. 1, pp. 494-501, 2005.
  64. Improving Generalization by Data Categorization. L. Li, A. Pratap, H.-T. Lin, and Y. Abu-Mostafa. In A. Jorge et al., eds., Knowledge Discovery in Databases: PKDD 2005, vol. 3721 of Lecture Notes in Artificial Intelligence, pp. 157-168. Springer-Verlag, 2005.
  65. Data Complexity in Machine Learning. L. Li and Y. Abu-Mostafa. Technical Report CaltechCSTR:2006.004, California Institute of Technology, May 2006. [CSTR]

Conference Keynotes

  1. Neural networks in foreign exchange (invited). Y. Abu-Mostafa. In Neural Networks in the Capital Markets (NNCM'93), London, UK, 1993.
  2. Validation of Volatility Models (invited). Y. Abu-Mostafa. In Neural Networks in the Capital Markets (NNCM'95), London, UK, 1995.
  3. The bin model for learning and generalization (keynote talk). Y. Abu-Mostafa. At International Conference on Neural Information Processing (ICONIP'96), Hong Kong, 1996. [archived conf web]
  4. Financial modeling and calibration (keynote). Y. Abu-Mostafa. In International Symposium on Intelligent Data Engineering and Learning (IDEAL'98), Hong Kong, October 1998. [conf web]
  5. Financial model calibration (keynote speech). Y. Abu-Mostafa. IEEE International Conference on Computational Intelligence for Financial Engineering (CIFEr2003), Hong Kong, March 2003.
  6. Exact generalization curves (keynote speech). Y. Abu-Mostafa, L. Li, and A. Nicholson. 7th Brazilian Congress on Neural Networks (CBRN VII), São Paulo, Brazil, June 2003.