Declarative recursive computation on an RDBMS: or, why you should use a database for distributed machine learning D Jankov, S Luo, B Yuan, Z Cai, J Zou, C Jermaine, ZJ Gao ACM SIGMOD Record 49 (1), 43-50, 2020 | 76 | 2020 |

Real-time high performance anomaly detection over data streams: Grand challenge D Jankov, S Sikdar, R Mukherjee, K Teymourian, C Jermaine Proceedings of the 11th ACM international conference on distributed and …, 2017 | 33 | 2017 |

Tensor relational algebra for distributed machine learning system design B Yuan, D Jankov, J Zou, Y Tang, D Bourgeois, C Jermaine Proceedings of the VLDB Endowment 14 (8), 2021 | 24 | 2021 |

Lachesis: Automated generation of persistent partitionings for big data applications J Zou, P Barhate, A Das, A Iyengar, B Yuan, D Jankov, C Jermaine Proc. VLDB Endowment 14, 1262-1275, 2021 | 15* | 2021 |

Automatic optimization of matrix implementations for distributed machine learning and linear algebra S Luo, D Jankov, B Yuan, C Jermaine Proceedings of the 2021 International Conference on Management of Data, 1222 …, 2021 | 13 | 2021 |

Tensor relational algebra for machine learning system design B Yuan, D Jankov, J Zou, Y Tang, D Bourgeois, C Jermaine arXiv preprint arXiv:2009.00524, 2020 | 13 | 2020 |

Distributed numerical and machine learning computations via two-phase execution of aggregated join trees D Jankov, B Yuan, S Luo, C Jermaine | 9 | 2021 |

SecNDP: Secure near-data processing with untrusted memory W Xiong, L Ke, D Jankov, M Kounavis, X Wang, E Northup, JA Yang, ... 2022 IEEE International Symposium on High-Performance Computer Architecture …, 2022 | 8 | 2022 |

Auto-differentiation of relational computations for very large scale machine learning Y Tang, Z Ding, D Jankov, B Yuan, D Bourgeois, C Jermaine International Conference on Machine Learning, 33581-33598, 2023 | 5 | 2023 |

Declarative Relational Machine Learning Systems D Jankov | | 2023 |