| Parallelized stochastic gradient descent M Zinkevich, M Weimer, L Li, AJ Smola Advances in neural information processing systems, 2595-2603, 2010 | 702 | 2010 |
| Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy N Koenigstein, G Dror, Y Koren Proceedings of the fifth ACM conference on Recommender systems, 165-172, 2011 | 456* | 2011 |
| Cofi rank-maximum margin matrix factorization for collaborative ranking M Weimer, A Karatzoglou, QV Le, AJ Smola Advances in neural information processing systems, 1593-1600, 2008 | 370 | 2008 |
| Improving maximum margin matrix factorization M Weimer, A Karatzoglou, A Smola Machine Learning 72 (3), 263-276, 2008 | 127 | 2008 |
| Automatically assessing the post quality in online discussions on software M Weimer, I Gurevych, M Mühlhäuser Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and …, 2007 | 112 | 2007 |
| Predicting the perceived quality of web forum posts M Weimer, I Gurevych Proceedings of the conference on recent advances in natural language …, 2007 | 59 | 2007 |
| Machine learning on big data T Condie, P Mineiro, N Polyzotis, M Weimer Data Engineering (ICDE), 2013 IEEE 29th International Conference on, 1242-1244, 2013 | 58 | 2013 |
| Scaling datalog for machine learning on big data Y Bu, V Borkar, MJ Carey, J Rosen, N Polyzotis, T Condie, M Weimer, ... arXiv preprint arXiv:1203.0160, 2012 | 57 | 2012 |
| Darmstadt knowledge processing repository based on UIMA I Gurevych, M Mühlhäuser, C Müller, J Steimle, M Weimer, T Zesch Proceedings of the First Workshop on Unstructured Information Management …, 2007 | 53 | 2007 |
| Iterative mapreduce for large scale machine learning J Rosen, N Polyzotis, V Borkar, Y Bu, MJ Carey, M Weimer, T Condie, ... arXiv preprint arXiv:1303.3517, 2013 | 38 | 2013 |
| Collaborative filtering on a budget A Karatzoglou, A Smola, M Weimer Proceedings of the Thirteenth International Conference on Artificial …, 2010 | 34 | 2010 |
| Declarative Systems for Large-Scale Machine Learning. VR Borkar, Y Bu, MJ Carey, J Rosen, N Polyzotis, T Condie, M Weimer, ... IEEE Data Eng. Bull. 35 (2), 24-32, 2012 | 33 | 2012 |
| Machine learning in ScalOps, a higher order cloud computing language M Weimer, T Condie, R Ramakrishnan NIPS 2011 Workshop on parallel and large-scale machine learning (BigLearn) 9 …, 2011 | 30 | 2011 |
| Reef: Retainable evaluator execution framework BG Chun, T Condie, C Curino, C Douglas, S Matusevych, B Myers, ... Proceedings of the VLDB Endowment 6 (12), 1370-1373, 2013 | 27 | 2013 |
| Adaptive collaborative filtering M Weimer, A Karatzoglou, A Smola Proceedings of the 2008 ACM conference on Recommender systems, 275-282, 2008 | 24 | 2008 |
| Towards geo-distributed machine learning I Cano, M Weimer, D Mahajan, C Curino, GM Fumarola arXiv preprint arXiv:1603.09035, 2016 | 19 | 2016 |
| Reef: Retainable evaluator execution framework M Weimer, Y Chen, BG Chun, T Condie, C Curino, C Douglas, Y Lee, ... Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 19 | 2015 |
| Maximum margin matrix factorization for code recommendation M Weimer, A Karatzoglou, M Bruch Proceedings of the third ACM conference on Recommender systems, 309-312, 2009 | 18 | 2009 |
| Towards resource-elastic machine learning S Narayanamurthy, M Weimer, D Mahajan, T Condie, S Sellamanickam, ... NIPS 2013 BigLearn Workshop, 2013 | 14 | 2013 |
| A convenient framework for efficient parallel multipass algorithms M Weimer, S Rao, M Zinkevich LCCC: NIPS 2010 Workshop on Learning on Cores, Clusters and Clouds, 2010 | 14 | 2010 |
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