Big Data and Systems

Big Data and Systems

  • Computational and statistical tradeoffs via convex relaxation. V. Chandrasekaran and M. I. Jordan. Proceedings of the National Academy of Sciences, doi:10.1073/pnas.1302293110, 2013.

  • Local privacy and statistical minimax rates. J. Duchi, M. I. Jordan, and M. Wainwright. arXiv:1302.3203, 2013.

  • The Big Data bootstrap. A. Kleiner, A. Talwalkar, P. Sarkar, and M. I. Jordan. In J. Langford and J. Pineau (Eds.), Proceedings of the 29th International Conference on Machine Learning (ICML), Edinburgh, UK, 2012.

  • Divide-and-conquer matrix factorization. L. Mackey, A. Talwalkar and M. I. Jordan. arXiv:1107.0789, 2012.

  • Small-variance asymptotics for exponential family Dirichlet process mixture models. K. Jiang, B. Kulis, and M. I. Jordan. In P. Bartlett, F. Pereira, L. Bottou and C. Burges (Eds.), Advances in Neural Information Processing Systems (NIPS) 24, in press.

  • Privacy aware learning. J. Duchi, M. I. Jordan, and M. Wainwright. In P. Bartlett, F. Pereira, L. Bottou and C. Burges (Eds.), Advances in Neural Information Processing Systems (NIPS) 24, in press.

  • Revisiting k-means: New algorithms via Bayesian nonparametrics. B. Kulis and M. I. Jordan. In J. Langford and J. Pineau (Eds.), Proceedings of the 29th International Conference on Machine Learning (ICML), Edinburgh, UK, 2012.

  • Bayesian bias mitigation for crowdsourcing. F. L. Wauthier and M. I. Jordan. In P. Bartlett, F. Pereira, J. Shawe-Taylor and R. Zemel (Eds.) Advances in Neural Information Processing Systems (NIPS) 24, 2012.

  • A scalable bootstrap for massive data. A. Kleiner, A. Talwalkar, P. Sarkar and M. I. Jordan. arXiv:1112.5016, 2011.

  • Divide-and-conquer matrix factorization. L. Mackey, A. Talwalkar and M. I. Jordan. In P. Bartlett, F. Pereira, J. Shawe-Taylor and R. Zemel (Eds.) Advances in Neural Information Processing Systems (NIPS) 24, 2012.

  • The SCADS Director: Scaling a distributed storage system under stringent performance requirements. B. Trushkowsky, P. Bodik, A. Fox, M. Franklin, M. I. Jordan, and D. Patterson. In 9th USENIX Conference on File and Storage Technologies (FAST '11), San Jose, CA, 2011.

  • Bayesian inference for queueing networks and modeling of Internet services. C. Sutton and M. I. Jordan. Annals of Applied Statistics, 5, 254-282, 2011.

  • Managing data transfers in computer clusters with Orchestra. M. Chowdhury, M. Zaharia, J. Ma, M. I. Jordan, and I. Stoica (2011). ACM SIGCOMM, Toronto, Canada, 2011.

  • Detecting large-scale system problems by mining console logs. W. Xu, L. Huang, A. Fox, D. Patterson, and M. I. Jordan. Proceedings of the 27th International Conference on Machine Learning (ICML), Haifa, Israel, 2010.

  • Characterizing, modeling, and generating workload spikes for stateful services. P. Bodik, A. Fox, M. Franklin, M. I. Jordan, and D. Patterson. First ACM Symposium on Cloud Computing (SOCC), Indianapolis, IN, 2010.

  • Large-scale system problems detection by mining console logs. W. Xu, L. Huang, A. Fox, D. Patterson, and M. I. Jordan. 22nd ACM Symposium on Operating Systems Principles (SOSP), Big Sky, MT, 2009.

  • Online system problem detection by mining patterns of console logs. W. Xu, L. Huang, A. Fox, D. Patterson, and M. I. Jordan. IEEE International Conference on Data Mining (ICDM), Miami, FL, 2009.

  • Automatic exploration of datacenter performance regimes. P. Bodik, R. Griffith, C. Sutton, A. Fox, M. I. Jordan, and D. Patterson. First Workshop on Automated Control for Datacenters and Clouds (ACDC), Barcelona, Spain, 2009.

  • Statistical machine learning makes automatic control practical for Internet datacenters. P. Bodik, R. Griffith, C. Sutton, A. Fox, M. I. Jordan, and D. Patterson. Workshop on Hot Topics in Cloud Computing (HotCloud), San Diego, CA, 2009.

  • Predicting multiple performance metrics for queries: Better decisions enabled by machine learning. A. Ganapathi, H. Kuno, U. Dayal, J. Wiener, A. Fox, M. I. Jordan, and D. Patterson. IEEE International Conference on Data Engineering (ICDE), Shanghai, China, 2009.

  • Probabilistic inference in queueing networks. C. A. Sutton and M. I. Jordan. Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SYSML), 2008.

  • Communication-efficient online detection of network-wide anomalies. L. Huang, X. Nguyen, M. Garofalakis, J. M. Hellerstein, M. I. Jordan, A. Joseph, and N. Taft. 26th Annual IEEE Conference on Computer Communications (INFOCOM'07), 2007.

  • In-network PCA and anomaly detection. L. Huang, X. Nguyen, M. Garofalakis, M. I. Jordan, A. Joseph, and N. Taft. In B. Schoelkopf, J. Platt and T. Hofmann (Eds.), Advances in Neural Information Processing Systems (NIPS) 19, 2007. [Long version].

  • Response-time modeling for resource allocation and energy-informed SLAs. P. Bodik, C. Sutton, A. Fox, D. Patterson, and M. I. Jordan. Workshop on Statistical Learning Techniques for Solving Systems Problems, Whistler, BC, 2007.

  • Statistical debugging: Simultaneous identification of multiple bugs. A. Zheng, M. I. Jordan, B. Liblit, M. Nayur, and A. Aiken. Proceedings of the 23rd International Conference on Machine Learning (ICML), 2006.

  • Scalable statistical bug isolation. B. Liblit, M. Naik, A. X. Zheng, A. Aiken, and M. I. Jordan. In press, ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2005. [Software]

  • Combining visualization and statistical analysis to improve operator confidence and efficiency for failure detection and localization. P. Bodik, G. Friedman, L. Biewald, H. Levine, G. Candea, K. Patel, G. Tolle, J. Hui, A. Fox, M. I. Jordan, and D. Patterson. International Conference on Autonomic Computing (ICAC), 2005.

  • Combining statistical monitoring and predictable recovery for self-management. A. Fox, E. Kiciman, D. A. Patterson, R. H. Katz and M. I. Jordan. ACM SIGSOFT Proceedings of the Workshop on Self-Managed Systems (WOSS), 2004.

  • Bug isolation via remote program sampling. B. Liblit, A. Aiken, A. X. Zheng, and M. I. Jordan. ACM SIGPLAN 2003 Conference on Programming Language Design and Implementation (PLDI), San Diego, 2003.

  • Public deployment of cooperative bug isolation. B. Liblit, A. Aiken, A. X. Zheng, and M. I. Jordan. Workshop on Remote Analysis and Measurement of Software Systems (RAMSS), 2004.

  • Statistical debugging of sampled programs. A. X. Zheng, M. I. Jordan, B. Liblit, and A. Aiken. In S. Thrun, L. Saul, and B. Schoelkopf (Eds.), Advances in Neural Information Processing Systems (NIPS) 16, 2004.

  • Failure diagnosis using decision trees. M. Chen, A. X. Zheng, J. Lloyd, M. I. Jordan, and E. Brewer. International Conference on Autonomic Computing (ICAC), 2004.

  • Sampling user executions for bug isolation. B. Liblit, A. Aiken, A. X. Zheng, and M. I. Jordan. Workshop on Remote Analysis and Measurement of Software Systems (RAMSS), 2003.

  • Stable algorithms for link analysis. A. Y. Ng, A. X. Zheng, and M. I. Jordan. Proceedings of the 24th International Conference on Research and Development in Information Retrieval (SIGIR), New York, NY: ACM Press, 2001.

  • Link analysis, eigenvectors, and stability. A. Y. Ng, A. X. Zheng, and M. I. Jordan. International Joint Conference on Artificial Intelligence (IJCAI), 2001.