Learning Theory and Its Applications




List of Publications(with review)

  1. A. Hirabayashi and H. Ogawa: ``Admissibility of memorization learning with respect to projection learning in the presence of noise,'' Proc. of Int. Conf. Neural Networks, 1, pp.335-340, Washington, D.C.(June 1996).

  2. A. Nakashima, A. Hirabayashi, and H. Ogawa: ``Noise suppression in training data for improving generalization,'' Proc. of Int. Joint Conf. Neural Networks, pp.2236-2241, Anchorage(May 1998).

  3. A. Hirabayashi, H. Ogawa, and Y. Yamashita: ``Admissibility of memorization learning with respect to projection learning in the presence of noise,'' IEICE Transactions on Information and Systems, E82-D, 2, pp.488-496(February 1999).

  4. A. Hirabayashi and H. Ogawa: ``A class of learning for optimal generalization,'' Proc. of Int. Joint Conf. on Neural Networks, 246 (CD-ROM), Washington, D.C.(July 1999).

  5. A. Hirabayashi and H. Ogawa: ``What can memorization learning do?'' Proc. of Int. Joint Conf. Neural Networks, 247 (CD-ROM), Washington, D.C.(July 1999).

  6. A. Hirabayashi, H. Ogawa, and A. Nakashima: ``Realization of admissibility of memorization learning with respect to projection learning,'' Proc. of LWA'99, Lernen, Wissensentdeckung und Adaptivitat (The GI-Workshop-Days Learning, Knowledge Discovery, and Adaptivity), Separate volume, pp.20-31, Magdeburg, Germany(September 1999).

  7. A. Hirabayashi and H. Ogawa: ``What can memorization learning do from noisy training examples?'' Proc. of 6th Int. Conf. Neural Information Processing, 1, pp.228-233, Perth(November 1999).

  8. A. Hirabayashi and H. Ogawa: ``Projection learning of the minimum variance type,'' Proc. of 6th Int. Conf. Neural Information Processing, 3, pp.1172-1177, Perth(November 1999).

  9. A. Hirabayashi, H. Ogawa, T. Mizutani, K. Nagai and K. Kitagawa: "Fast surface profiling by white-light interferometry using a sampling theorem for band-pass signals," The Transactions of SICE, Vol.36, No.1, pp.16-25, Jan. 2000 (in Japanese).

  10. A. Hirabayashi and H. Ogawa: "A family of projection learnings," IEICE Trans. (D-II), Vol.J83, No.2, pp.754-767, Feb. 2000 (in Japanese).

  11. A. Hirabayashi and H. Ogawa: "Applicability of memorization learning to a family of projection learnings," IEICE Trans. (D-II), Vol.J83, No.2, pp.768-775, Feb. 2000 (in Japanese).

  12. H. Iwaki, H. Ogawa, and A. Hirabayashi: "Optimally generalizing neural networks with ability to recover from single stuck-at r faults," IEICE Trans. (D-II), Vol.J83, No.2, pp.805-813, Feb. 2000 (in Japanese).

  13. A. Hirabayashi, H. Ogawa, and A. Nakashima: ``Realization of admissibility for supervised learning,'' IEICE Transactions on Information and Systems, E83-D, 5, pp.1170-1176(May 2000).

  14. A. Nakashima, A. Hirabayashi, and H. Ogawa: ``Error correcting memorization learning for noisy training data,'' Neural Networks, Vol.14, No.1, pp.79-92, 2001.

  15. H. Ogawa, A. Hirabayashi, and K. Kitagawa: ``Sampling theorem for surface profiling by white-light interferometry,'' Proc. of Int.Conf. of Sampling Theory and Applications, pp.91-96, Orlando, Florida, May 2001. (pdf)

  16. A. Hirabayashi, H. Ogawa, and K. Kitagawa: ``Fast surface profiler by white-light interferometry using a new algorithm, the SEST algorithm,'' in Optical Manufacturing and Testing IV, H.P. Stahl, ed., Proceedings of SPIE, Vol.4451, pp.356-367, San Diego, California, July 2001. (pdf)

  17. A. Hirabayashi:``Fast algorithm for surface profiling by white-light interferometry using an optical filter with symmetric spectral distribution,'' in Proceedings of the 2001 1st IEEE Conference on Nanotechnology (IEEE-NANO-2001), pp.459-464, Maui, Hawaii, October 2001. (pdf)

  18. H. Ogawa and A. Hirabayashi, ``Sampling theory in white-light interferometry,'' Sampling Theory in Signal and Image Processing, vol.1, no.2, pp.87-116 (May 2002).

  19. A. Hirabayashi, H. Ogawa, and K. Kitagawa, ``Fast surface profiler by white-light interferometry by use of a new algorithm based on sampling theory,'' Applied Optics, vol.41, no.23, pp.4876-4883 (August 2002).

  20. N. Iizuka, M. Oka, H. Okabe, M. Nishida, Y. Maeda, N. Mori, T. Takao, T. Tamesa, A. Tangoku, H. Tabuchi, K. Hamada, H. Nakayama, H. Ishitsuka, T. Miyamoto, A. Hirabayashi, S. Uchimura, and Y. Hamamoto, ``Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection,'' The Lancet, vol.361, no.9361, pp.923-929 (March 2003).

  21. A. Hirabayashi and H. Ogawa, ``Sampling theory with non-exact sampled values,'' in Proceedings of the 2003 International Conference on Sampling Theory and Applications (SampTA2003), p.45, Salzburg, Austria (May 2003).

  22. A. Hirabayashi, Y. Nakayama, H. Ogawa, and K. Kitagawa, ``Algorithm with optimum noise suppression for surface profiling by white-light interferometry,'' in Optical Manufacturing and Testing V, H.P. Stahl, ed., Proceedings of SPIE, vol.5180, pp.365-376, San Diego, California (July 2003).

  23. A. Hirabayashi and Michael Unser, ``An extension of oblique projection sampling theorem,'' in Proceedings of the 2005 International Conference on Sampling Theory and Applications (SampTA2005), CD-ROM, Samsun, Turkey (July 2005).

  24. A. Hirabayashi and T. Naito, ``Signal reconstruction by projection filter with preservation of preferential components,'' in Proceedings of the International Conference on Knowledge-Based \& Intelligent Information \& Engineering Systems (KES2006), Bournemouth, U.K., Part III, LNAI 4253, pp.1272-1279 (October 2006).

  25. A. Hirabayashi, ``Generalization of DFT and DCT from the viewpoint of sampling theory,'' in Proceedings of the 2007 International Conference on Sampling Theory and Applications (SampTA2007), CD-ROM, Thessaloniki, Greece (June 2007).

  26. A. Hirabayashi and L. Condat, ``A compact image magnification method with preservation of preferential components,'' in Proceedings of the International Conference on Image Processing (ICIP) (September 2007) (in press).

  27. A. Hirabayashi and L. Condat, ``Towards general formulation of over/under-sampling,'' in Proceedings of the European Signal Processing Conference (EUSIPCO) (September 2007) (in press).

  28. H. Ogawa and A. Hirabayashi, ``Sampling theory with optimum noise suppression,'' Sampling Theory in Signal and Image Processing, vol.6, no.2, pp.167-184 (May 2007).

  29. A. Hirabayashi and Michael Unser, ``Consistent sampling and signal recovery,'' IEEE Transactions on Signal Processing (in press).

  30. A. Hirabayashi, ``Image magnification by a compact method with preservation of preferential components,'' IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (in press).


Home


Copyright(c) 2003 the Pattern Recognition Group at Dept. of Computer Science and Systems Engineering, Faculty of Engineering Yamaguchi University