| Revisiting distributed synchronous SGD J Chen, X Pan, R Monga, S Bengio, R Jozefowicz arXiv preprint arXiv:1604.00981, 2016 | 925 | 2016 |
| Perturbed iterate analysis for asynchronous stochastic optimization H Mania, X Pan, D Papailiopoulos, B Recht, K Ramchandran, MI Jordan SIAM Journal on Optimization 27 (4), 2202-2229, 2017 | 258 | 2017 |
| MLI: An API for distributed machine learning ER Sparks, A Talwalkar, V Smith, J Kottalam, X Pan, J Gonzalez, ... 2013 IEEE 13th International Conference on Data Mining, 1187-1192, 2013 | 244 | 2013 |
| City-scale traffic estimation from a roving sensor network J Aslam, S Lim, X Pan, D Rus Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems …, 2012 | 203 | 2012 |
| SALSA: Analyzing logs as state machines J Tan, X Pan, S Kavulya, R Gandhi, P Narasimhan First USENIX Workshop on Analysis of System Logs (WASL), 2008 | 167 | 2008 |
| Ganesha: Black-box diagnosis of MapReduce systems X Pan, J Tan, S Kavulya, R Gandhi, P Narasimhan ACM SIGMETRICS Performance Evaluation Review 37 (3), 8-13, 2010 | 122 | 2010 |
| Parallel correlation clustering on big graphs X Pan, D Papailiopoulos, S Oymak, B Recht, K Ramchandran, MI Jordan Advances in Neural Information Processing Systems 28, 2015 | 107 | 2015 |
| Mochi: Visual log-analysis based tools for debugging hadoop J Tan, X Pan, S Kavulya, R Gandhi, P Narasimhan Hot Topics in Cloud Computing (HotCloud), 2009 | 101 | 2009 |
| Kahuna: Problem diagnosis for mapreduce-based cloud computing environments J Tan, X Pan, E Marinelli, S Kavulya, R Gandhi, P Narasimhan Network Operations and Management Symposium (NOMS), 112-119, 2010 | 96 | 2010 |
| Cyclades: Conflict-free asynchronous machine learning X Pan, M Lam, S Tu, D Papailiopoulos, C Zhang, MI Jordan, ... Advances in Neural Information Processing Systems, 2016, 2016 | 65 | 2016 |
| Parallel double greedy submodular maximization X Pan, S Jegelka, J Gonzalez, J Bradley, M Jordan Advances in Neural Information Processing Systems 26, 2014 | 44 | 2014 |
| Optimistic concurrency control for distributed unsupervised learning X Pan, JE Gonzalez, S Jegelka, T Broderick, MI Jordan Advances in Neural Information Processing Systems 26, 2013 | 36 | 2013 |
| Hemingway: modeling distributed optimization algorithms X Pan, S Venkataraman, Z Tai, J Gonzalez arXiv preprint arXiv:1702.05865, 2017 | 32 | 2017 |
| Twitter homophily: Network based prediction of user’s occupation J Pan, R Bhardwaj, W Lu, HL Chieu, X Pan, NY Puay Proceedings of the 57th Conference of the Association for Computational …, 2019 | 27 | 2019 |
| MLbase: A distributed machine learning wrapper A Talwalkar, T Kraska, R Griffith, J Duchi, J Gonzalez, D Britz, X Pan, ... Big Learning Workshop at NIPS, 2012 | 22* | 2012 |
| Blind men and the elephant: Piecing together Hadoop for diagnosis X Pan, J Tan, S Kavulya, R Gandhi, P Narasimhan International Symposium on Software Reliability Engineering (ISSRE), Mysuru …, 2009 | 18 | 2009 |
| ASDF: Automated online fingerpointing for Hadoop K Bare, M Kasick, S Kavulya, E Marinelli, X Pan, J Tan, R Gandhi, ... Technical Report CMU-PDL-08-104, Carnegie Mellon, 2008 | 16* | 2008 |
| A cognitive system for adaptive decision making X Pan, LN Teow, KH Tan, JHB Ang, GW Ng Proceedings of the 15th International Conference on Information Fusion …, 2012 | 12 | 2012 |
| Ganesha: Black-box fault diagnosis for MapReduce systems X Pan, J Tan, S Kavulya, R Gandhi, P Narasimhan Hot Metrics, 2008 | 10 | 2008 |
| Parallel machine learning using concurrency control X Pan UC Berkeley, 2017 | 2 | 2017 |
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley在 cs.berkeley.edu 的电子邮件经过验证
