Publications

2001

  • Kanapady, R., S. K. Bathina, K.K. Tamma, C. Kamath, and V. Kumar, “Determination of an initial mesh density for finite element computations via data mining,” Proceedings of the Fourth Workshop on Mining Scientific Datasets, pp. 64-70, KDD 2001, August 2001. Also available as Lawrence Livermore National Laboratory technical report, UCRL-JC-144765.
  • Sandhu, S.S., R. Kanapady, K.K. Tamma, C. Kamath, and V. Kumar, “Damage Prediction and estimation in structural mechanics based on data mining,” Proceedings of the Fourth Workshop on Mining Scientific Datasets, KDD 2001, pp 56-63, August 2001. Also available as Lawrence Livermore National Laboratory technical report, UCRL-JC-144764.
  • C. Kamath, Proceedings of the Fourth Workshop on Mining Scientific Datasets (ed.), August 2001, KDD2001. Also available as Lawrence Livermore National Laboratory technical report, UCRL-ID-144763.
  • Fodor, I. K., and C. Kamath, “Dimension reduction techniques and the Classification of Bent Double Galaxies,” Computational Statistics and Data Analysis journal, Volume 41, pp. 91-122, 2002.
  • Fodor, I. K., and C. Kamath, “Denoising through Wavelet Shrinkage: An Empirical Study,” SPIE Journal on Electronic Imaging, Vol. 12, No. 1, pp. 151-160, January 2003.
  • R. Grossman, C. Kamath, W. Kegelmeyer, V. Kumar, and R. Namburu eds., Data Mining for Scientific and Engineering Applications, Kluwer, September 2001.
  • E. Cantú-Paz, and C. Kamath, “Inducing Oblique Decision Trees with Evolutionary Algorithms,” IEEE Transactions on Evolutionary Computing, Volume 7, No. 1, pp. 54-68, February 2003.
  • Kamath, C., E. Cantu-Paz, I. K. Fodor, N. Tang, “Using data mining to find bent-double galaxies in the FIRST survey,” Proceedings, Astronomical Data Analysis, at the SPIE Annual Meeting, San Diego, July-August 2001.
  • Kamath, C., and E. Cantu-Paz, Creating ensembles of decision trees through sampling, Proceedings, 33rd Symposium on the Interface of Computing Science and Statistics, Costa Mesa, CA, June 2001.
  • Fodor, I. K., and C. Kamath, “A comparison of de-noising techniques for FIRST images,” Proceedings, Third workshop on Mining Scientific Datasets, held in conjunction with the First SIAM Int. Conf. on Data Mining, Chicago, April 2001, pp. 13-20.
  • Fodor, I. K., and C. Kamath, “On Denoising Images Using Wavelet-based Statistical Techniques,” Lawrence Livermore National Laboratory technical report, UCRL JC-142357.
  • Kamath, C., “The Role of Parallel and Distributed Processing in Data Mining,” Spring 2001 newsletter of the IEEE Technical Committee on Distributed Processing, pp. 10-15. Also available as Lawrence Livermore National Laboratory technical report, UCRL-JC-142468.
  • Cantu-Paz, E., and C. Kamath, “On the Use of Evolutionary Algorithms in Data Mining,” book chapter in Data Mining: A Heuristic Approach, Eds. H. Abbass, R. Sarker, and C. Newton, pp. 48-71, 2001.
  • C. Kamath, “On Mining Scientific Datasets,” book chapter in Data Mining for Scientific and Engineering Applications, eds. R. Grossman, C. Kamath, P. Kegelmeyer, V. Kumar, and R. Namburu, Kluwer, pp. 1-22, 2001.
  • Kamath, C, E., Cantu-Paz, I. K. Fodor, N. Tang, “Searching for Bent-Double Galaxies in the FIRST Survey,” book chapter in Data Mining for Scientific and Engineering Applications, eds. R. Grossman, C. Kamath, W. Kegelmeyer, V. Kumar, and R. Namburu, Kluwer, pp. 95-114, 2001.
  • Fodor, Imola, and Chandrika Kamath, “The Role of Multiresolution in Mining Massive Image Datasets,” in Multiscale and Multiresolution Methods, Lecture Notes in Computational Science and Engineering, T. J. Barth, T. Chan, and R. Haimes, (Eds.), Volume 20, Springer-Verlag, pp. 307-318, 2001.

2000

  • Kamath, C., and Ann Parker, “Mining Data for Gems of Information,” Research Highlight, Science and Technology Review, September 2000, pages 20-22. UCRL-52000-00-9.
  • Kamath, Chandrika, and Erick Cantú-Paz, “On the design of a parallel object-oriented data mining toolkit, “Workshop on Distributed and Parallel Knowledge Discovery, at the Knowledge Discovery and Data Mining Conf., Boston, August 20-23, 2000.
  • Cantú-Paz, E., and Kamath, C. “Combining evolutionary algorithms with oblique decision trees to detect bent double galaxies,” in Conf. Proc. Int. Symposium on Optical Science and Technology, SPIE Annual Meeting, Vol. 4120, pp. 63-71, San Diego, July 30-August 4, 2000.
  • Kamath, Chandrika, Chuck Baldwin, Imola Fodor, and Nu Ai Tang, “On the design and implementation of a parallel, object-oriented, image processing toolkit,” Proc. Int. Symp. on Optical Science & Technology, SPIE Annual Meeting, San Diego, July 30-August 4, 2000.
  • Kargupta, Hillol, Chandrika Kamath, and Philip Chan, Distributed and Parallel Data Mining: Emergence, Growth, and Future Directions, epilogue in Advances in Distributed and Parallel Knowledge Discovery, AAAI Press/MIT Press, pages 409-417, 2000.
  • Cantú-Paz, Erick, and Chandrika Kamath, “Using Evolutionary Algorithms to Induce Oblique Decision Trees,” Genetic and Evolutionary Computation Conf. (GECCO) 2000, Las Vegas, NV, July 8-12, 2000.
  • Fodor, Imola, Erick Cantú-Paz, Chandrika Kamath, and Nu Ai Tang, “Finding Bent-Double Radio Galaxies: A Case Study in Data Mining, “Interface: Computer Science and Statistics, Volume 33, New Orleans, LA, April 2000.

1999

  • Kamath, Chandrika, and Ron Musick, “Scalable Data Mining through Fine-Grained parallelism: The Present and the Future,” in Advances in Distributed and Parallel Knowledge Discovery H. Kargupta and P. Chan, Eds., (AAAI Press/MIT Press), pages 29-77, 2000.
  • Kamath, Chandrika, and Ron Musick, “Data Mining for Large, Complex Data Sets,” a position paper in Mining and Managing Massive Data Sets ‘98, La Jolla, CA, February 5-6, 1998. Also available as Lawrence Livermore National Laboratory technical report. UCRL-JC-129727.
  • Kamath, Chandrika, SAPPHIRE: Large-Scale Data Mining and Pattern Recognition, Lawrence Livermore National Laboratory technical brochure UCRL-TB-132076, January 1999.

Pre-1999

  • Chandrika Kamath Roy Ho, Dwight P. Manley, “DXML: a high-performance scientific subroutine library,” Digital Technical Journal Volume 6, Issue 3, Summer 1994, pp. 44–56.
  • Chandrika Kamath and Ahmed Sameh, “A Projection Method for Solving Nonsymmetric Linear Systems on Multiprocessors,” Parallel Computing , Vol. 9, pp. 291-312, 1989.
  • C. Kamath, A. H. Sameh, G. C. Yang and D. J. Kuck, “Structural Computations on the Cedar System,” Computers and Structures, Vol. 20, No. 1-3, pp. 47-54, 1985.
  • C. Kamath and A. Sameh, “The Preconditioned Conjugate Gradient Algorithm on a Multiprocessor,” Fifth IMACS International Symp. on Computer Methods for Partial Differential Equations, pp. 210-217, June, 1984.
  • Chandrika, Kamath and V.C. Bhavsar, ‘Implementation and Performance Prediction of Some Parallel Algorithms on PLEXUS Microcomputer Network’ Microprocessing and Microprogramming, Vol. 10, pp. 25-31, 1982.