Inference and learning in networks of queues

Journal of Machine Learning Research

Volumn 9, Issue , 2010, Pages 796-803

  Sutton, Charles ^a   Jordan, Michael I ^b  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GRAPHICAL MODEL; MARKOV CHAIN MONTE CARLO; MISSING DATA; PERFORMANCE MODEL; PERFORMANCE OF COMPUTER SYSTEM; PERFORMANCE PROBLEMS; PROBABILISTIC MODELS; REAL WORLD DATA; WEB APPLICATION;

ARTIFICIAL INTELLIGENCE; PARAMETER ESTIMATION;

QUEUEING THEORY;

EID: 84862282235     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (9)

1. R. Castro, M. Coates, G. Liang, R. Nowak, and B. Yu. Network tomography: Recent developments. Statistical Science, 2004.
2. P. Fearnhead. Filtering recursions for calculating likelihoods for queues based on inter-departure time data. Statistics and Computing, 14(3):261-266, 2004.
3. K. Heggland and A. Frigessi. Estimating functions in indirect inference. Journal of the Royal Statistical Society. Series B, 66(2):447-462, 2004.
4. L. K. Jones. Inferring balking behavior from transactional data. Operations Research, 47(5):778-784, 1999.
5. L. Kleinrock. Queueing Systems: Theory and Applications. Wiley Interscience, New York, 1973.
6. R. M. Neal. Slice sampling. The Annals of Statistics, 31 (3):705-741, 2003.
7. W. Sobel, S. Subramanyam, A. Sucharitakul, J. Nguyen, H. Wong, S. Patil, A. Fox, and D. Patterson. Cloud-stone: Multi-platform, multi-language benchmark and measurement tools for Web 2.0. In First Workshop on Cloud Computing and its Applications (CCA), 2008.
8. B. Urgaonkar, G. Pacifici, P. Shenoy, M. Spreitzer, and A. Tantawi. An analytical model for multi-tier internet services and its applications. In SIGMETRICS, 2005.
9. M. Welsh. An Architecture for Highly Concurrent, Well-Conditioned Internet Services. PhD thesis, University of California, Berkeley, 2002.