HiLighter: Automatically building robust signatures of performance behavior for small- And large-scale systems

3rd Workshop on Tackling Computer Systems Problems with Machine Learning Techniques, SysML 2008

Volumn , Issue , 2008, Pages

  Bodík, Peter ^a   Goldszmidt, Moises ^b   Fox, Armando ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LARGE SCALE SYSTEMS; LOGISTIC REGRESSION; MACHINE LEARNING;

ENTERPRISE SYSTEM; INTERNET SERVERS; INTERNET SERVICES; L1 REGULARIZATIONS; NUMBER OF SAMPLES; OPERATIONAL PROBLEMS; SIMILARITY SEARCH; STATISTICAL TECHNIQUES;

NETWORK SECURITY;

EID: 85092756805     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. G. Andrew and J. Gao. Scalable training of L1-regularized log-linear models. In Z. Ghahramani, editor, Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007), pages 33-40. Omnipress, 2007.
2. I. Cohen, S. Zhang, M. Goldszmidt, J. Symons, T. Kelly, and A. Fox. Capturing, indexing, clustering, and retrieving system history. In A. Herbert and K. P. Birman, editors, SOSP, pages 105-118. ACM, 2005.
3. G. Cretu, M. Budiu, and M. Goldszmidt. Hunting for problems with Artemis. Technical report, Microsoft, 2008.
4. N. Friedman, D. Geiger, and M. Goldszmidt. Bayesian network classifiers. Mach. Learn., 29(2-3):131-163, 1997.
5. S. R. Garner. Weka: The Waikato Environment for Knowledge Analysis. In In Proc. of the New Zealand Computer Science Research Students Conference, pages 57-64, 1995.
6. K. Koh, S.-J. Kim, and S. Boyd. An interior-point method for large-scale L1-regularized logistic regression. Journal of Machine Learning Research, 8:1519-1555, 2007.
7. A. Ng. Feature selection, L1 vs. L2 regularization, and rotational invariance. In Proceedings of the 21st Annual International Conference on Machine Learning (ICML 2004), 2004.
8. L. Wasserman. All of statistics. Springer, 2004.
9. M. Young and P. T. Hastie. L1 regularization path algorithm for generalized linear models, 2006.
10. Y. Yu, M. Isard, D. Fetterly, M. Budiu, Ú. Erlingsson, P. K. Gunda, and J. Currey. DryadLINQ: A system for general-purpose distributed data-parallel computing using a high-level language. In Symposium on Operating System Design and Implementation (OSDI), San Diego, CA, December 8-10 2008.