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SENSORWEBS PROJECT

> publications


This is a sampling of the related research papers.

Systems:

  • L. Doherty, Algorithms for Position and Data Recovery in Wireless Sensor Networks, UC Berkeley EECS Masters Report, May 2000 [pdf]

Distributed Source Coding:

  • S.Sandeep Pradhan and Kannan Ramchandran, Distributed source coding using syndromes (DISCUS): Design and construction, Proc. IEEE Data Compression Conference (DCC), 1999 [ps]
  • S.Sandeep Pradhan and Kannan Ramchandran, Distributed source coding: Symmetric rates and applications to sensor networks, Proc. IEEE Data Compression conference (DCC), March 2000 [ps]
  • J. Kusuma, L. Doherty and Kannan Ramchandran, Distributed source coding for sensor networks, Proc. IEEE Conf. on Image Processing (ICIP), October 2001 [ps]

Artificial Intelligence and Learning Theory:

  • A. Y. Ng, and M. I. Jordan, Approximate inference algorithms for two-layer Bayesian networks, Advances in Neural Information Processing Systems 11. Cambridge MA: MIT Press [ps]
  • L. K. Saul, and M. I. Jordan, Attractor dynamics for feedforward neural networks, Neural Computation, 12, 1313-1335, 2000 [ps]
  • T. S. Jaakkola, and M. I. Jordan, Bayesian parameter estimation via variational methods, Statistics and Computing, 10, 25-37, 2000 [ps]
  • T. S. Jaakkola, and M. I. Jordan, Variational probabilistic inference and the QMR-DT network,  Journal of Artificial Intelligence Research, 10, 291-322, 1999 [ps]
  • M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul, An introduction to variational methods for graphical models, Machine Learning, 37, 183-233, 1999 [ps]

 

   

contact: julius kusuma