References
- Akyildiz , I. F. and Su , W. 2002 . Sankarasubramanian and Cayirci, Wireless sensor networks: a survey . Computer Networks , 38 ( 4 ) March : 393 – 422 .
- Bermak , A. and Belhouari , S. B. 2006 . Bayesian Learning using Gaussian Process for Gas Identification
- Chen-Kong , T. and Buyya , R. July 2005 . Sensor Grid: Integrating Sensor Networks and Grid Computing July ,
- Ferns , B. , Fox , D. and Lawrence , N. December 2006 . 15WiFi-SLAM Using Gaussian Process Latent Variable Models , December , University of Washington, Department of Computer & Engineering; University of Sheffield, Department of Computer Science .
- Freidman , N. , Geiger , D. and Goldesmidt , M. 1997 . Bayesian network classifiers . Machine Learning , 29 : 131 – 163 .
- Friedman , N. and Nachman , I. 2003 . Gaussian Process Networks
- Deshpande , A. , Gunstrin , C. , Madden , S. , Hellerstein , J. and Hong , W. 2004 . Model-driven Data Acquisition in Sensor Networks VLDB
- Duate , M. F. and Yit , H. 2003 . “ Optimal decision fusion for sensor network applications ” . In Int. Proceedings of 1st ACM Conference an Embedded Networked Sensor Systems (SenSys 2003).
- Geiger and Heckerman , D. 1994 . Learning Gaussian Networks , MSR_TR-94-10, Microsoft Research
- Grossman , D. and Domingos , P. Learning Bayesian Network Classifiers by Maximizing Conditional Independence and Bayesian Networks
- Guestrin , C. , Krause , A. and Singh , A. P. Near Optimal Sensor Placements in Gaussian Processes
- Rasmussen , A. Girard , Candela , J. Q. and Murray-Smith , R. Gaussian Process Priors with Uncertain Inputs – Application to Multiple-Step Ahead Time Series Forecasting
- Golub , G. and Van Loan , C. 1989 . Matrix Computations , Johns Hopkins .
- Heckerman , D. March 1985 . A Tutorial on Learning with Bayesian Networks , March , Microsoft Research Advanced Technology Division, Microsoft Corporation . (revised November, 1996).
- Jordan , I. M. and Wiess , Y. 2005 . Probabilistic inference in graphical models
- Seeger , M. February 24 2004 . Gaussian Processes for Machine learning , February 24 , CA , , USA : Berkeley .
- Ko , C. , Lee , J. and Queyranne , N. 1995 . An act algorithm for maximum entropy sampling . Ops Research , 43 : 684 – 691 .
- Mercer , J. 1909 . Functions of positive and negative type and then – connection with the theory of integral equations . Philos. Trans. Roy. Soc. London ,
- Niedermayer , D. December 1 1998 . An Introduction to Bayesian Networks and their Contemporary Applications December 1 ,
- Rausmussen , C. E. 2006 . Gaussian Processes Covariance Functions and Classification
- Rasmussen , C. E. Gaussian Processes in Machine Learning
- Robert , A. 1990 . Information Theory , Dover Publications .
- Williams , C. K. and Rausmussen , C. E. 1996 . “ Gaussian processes for regression ” . In NIPS in