| Seedb: Efficient data-driven visualization recommendations to support visual analytics M Vartak, S Rahman, S Madden, A Parameswaran, N Polyzotis Proceedings of the VLDB Endowment International Conference on Very Large …, 2015 | 302 | 2015 |
| ModelDB: a system for machine learning model management M Vartak, H Subramanyam, WE Lee, S Viswanathan, S Husnoo, ... Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 1-3, 2016 | 287 | 2016 |
| A meta-learning perspective on cold-start recommendations for items M Vartak, A Thiagarajan, C Miranda, J Bratman, H Larochelle Advances in neural information processing systems 30, 2017 | 273 | 2017 |
| On challenges in machine learning model management S Schelter, F Biessmann, T Januschowski, D Salinas, S Seufert, ... | 224 | 2015 |
| Towards visualization recommendation systems M Vartak, S Huang, T Siddiqui, S Madden, A Parameswaran Acm Sigmod Record 45 (4), 34-39, 2017 | 166 | 2017 |
| A demonstration of the bigdawg polystore system AJ Elmore, J Duggan, M Stonebraker, M Balazinska, U Cetintemel, ... Proceedings of the VLDB Endowment 8 (12), 1908, 2015 | 146 | 2015 |
| SEEDB: automatically generating query visualizations M Vartak, S Madden, A Parameswaran, N Polyzotis Association for Computing Machinery (ACM), 2014 | 109 | 2014 |
| The Assistment Builder: Supporting the life cycle of tutoring system content creation L Razzaq, J Patvarczki, SF Almeida, M Vartak, M Feng, NT Heffernan, ... IEEE Transactions on Learning Technologies 2 (2), 157-166, 2009 | 102 | 2009 |
| Mistique: A system to store and query model intermediates for model diagnosis M Vartak, JM F. da Trindade, S Madden, M Zaharia Proceedings of the 2018 International Conference on Management of Data, 1285 …, 2018 | 75 | 2018 |
| Modeldb: Opportunities and challenges in managing machine learning models. M Vartak, S Madden IEEE Data Eng. Bull. 41 (4), 16-25, 2018 | 57 | 2018 |
| Genbase: A complex analytics genomics benchmark R Taft, M Vartak, NR Satish, N Sundaram, S Madden, M Stonebraker Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014 | 45 | 2014 |
| September 2015. Seedb: Efficient data-driven visualization recommendations to support visual analytics M Vartak, S Rahman, S Madden, A Parameswaran, N Polyzotis PVLDB 8 (13), 2182-2193, 0 | 42 | |
| Supporting fast iteration in model building M Vartak, P Ortiz, K Siegel, H Subramanyam, S Madden, M Zaharia NIPS Workshop LearningSys, 1-6, 2015 | 28 | 2015 |
| Qrelx: generating meaningful queries that provide cardinality assurance M Vartak, V Raghavan, EA Rundensteiner Proceedings of the 2010 ACM SIGMOD International Conference on Management of …, 2010 | 27 | 2010 |
| CHIC: a combination-based recommendation system M Vartak, S Madden Proceedings of the 2013 ACM SIGMOD International Conference on Management of …, 2013 | 19 | 2013 |
| Smallify: Learning network size while training G Leclerc, M Vartak, RC Fernandez, T Kraska, S Madden arXiv preprint arXiv:1806.03723, 2018 | 17 | 2018 |
| Refinement driven processing of aggregation constrained queries M Vartak, V Raghavan, E Rundensteiner, S Madden | 12 | 2016 |
| Infrastructure for model management and model diagnosis M Vartak Massachusetts Institute of Technology, 2018 | 5 | 2018 |
| From ml models to intelligent applications: the rise of mlops M Vartak Proceedings of the VLDB Endowment 14 (13), 3419-3419, 2021 | 4 | 2021 |
| Opportunities for data management research in the era of horizontal AI/ML T Rekatsinas, S Roy, M Vartak, C Zhang, N Polyzotis Proceedings of the VLDB Endowment 12 (12), 2323-2323, 2019 | 3 | 2019 |
