| Parallelized stochastic gradient descent M Zinkevich, M Weimer, L Li, A Smola Advances in neural information processing systems 23, 2010 | 1850 | 2010 |
| Cofi rank-maximum margin matrix factorization for collaborative ranking M Weimer, A Karatzoglou, Q Le, A Smola Advances in neural information processing systems 20, 2007 | 535 | 2007 |
| The yahoo! music dataset and kdd-cup’11 G Dror, N Koenigstein, Y Koren, M Weimer Proceedings of KDD Cup 2011, 3-18, 2012 | 365 | 2012 |
| On challenges in machine learning model management S Schelter, F Biessmann, T Januschowski, D Salinas, S Seufert, ... | 233 | 2015 |
| Flaml: A fast and lightweight automl library C Wang, Q Wu, M Weimer, E Zhu Proceedings of Machine Learning and Systems 3, 434-447, 2021 | 218 | 2021 |
| Improving maximum margin matrix factorization M Weimer, A Karatzoglou, A Smola Machine Learning 72, 263-276, 2008 | 171 | 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 Association for Computational …, 2007 | 144 | 2007 |
| {PRETZEL}: Opening the black box of machine learning prediction serving systems Y Lee, A Scolari, BG Chun, MD Santambrogio, M Weimer, M Interlandi 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018 | 140 | 2018 |
| Learning to solve circuit-sat: An unsupervised differentiable approach S Amizadeh, S Matusevych, M Weimer International Conference on Learning Representations, 2019 | 118 | 2019 |
| Machine learning for big data T Condie, P Mineiro, N Polyzotis, M Weimer Proceedings of the 2013 ACM SIGMOD International Conference on Management of …, 2013 | 118 | 2013 |
| Extending relational query processing with ML inference K Karanasos, M Interlandi, D Xin, F Psallidas, R Sen, K Park, I Popivanov, ... arXiv preprint arXiv:1911.00231, 2019 | 89 | 2019 |
| Machine learning at Microsoft with ML. NET Z Ahmed, S Amizadeh, M Bilenko, R Carr, WS Chin, Y Dekel, X Dupre, ... Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 85 | 2019 |
| Towards geo-distributed machine learning I Cano, M Weimer, D Mahajan, C Curino, GM Fumarola arXiv preprint arXiv:1603.09035, 2016 | 76 | 2016 |
| 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 | 76 | 2012 |
| Predicting the perceived quality of web forum posts M Weimer, I Gurevych Proceedings of the Conference on Recent Advances in Natural Language …, 2007 | 76 | 2007 |
| 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 | 71 | 2007 |
| Data science through the looking glass: Analysis of millions of github notebooks and ml. net pipelines F Psallidas, Y Zhu, B Karlas, J Henkel, M Interlandi, S Krishnan, B Kroth, ... ACM SIGMOD Record 51 (2), 30-37, 2022 | 65 | 2022 |
| A tensor compiler for unified machine learning prediction serving S Nakandala, K Saur, GI Yu, K Karanasos, C Curino, M Weimer, ... 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020 | 63 | 2020 |
| Vamsa: Automated provenance tracking in data science scripts MH Namaki, A Floratou, F Psallidas, S Krishnan, A Agrawal, Y Wu, Y Zhu, ... Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 62 | 2020 |
| Collaborative filtering on a budget A Karatzoglou, A Smola, M Weimer Proceedings of the Thirteenth International Conference on Artificial …, 2010 | 58 | 2010 |
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