| Explainable k-means and k-medians clustering M Moshkovitz, S Dasgupta, C Rashtchian, N Frost International conference on machine learning, 7055-7065, 2020 | 272 | 2020 |
| ExKMC: Expanding Explainable -Means Clustering N Frost, M Moshkovitz, C Rashtchian arXiv preprint arXiv:2006.02399, 2020 | 100 | 2020 |
| Framework for Evaluating Faithfulness of Local Explanations S Dasgupta, N Frost, M Moshkovitz Proceedings of the 39th International Conference on Machine Learning 162 …, 2022 | 97 | 2022 |
| Computing the shapley value of facts in query answering D Deutch, N Frost, B Kimelfeld, M Monet Proceedings of the 2022 International Conference on Management of Data, 1570 …, 2022 | 55 | 2022 |
| Provenance for natural language queries D Deutch, N Frost, A Gilad Proceedings of the VLDB Endowment 10 (5), 577-588, 2017 | 45 | 2017 |
| Constraints-based explanations of classifications D Deutch, N Frost 2019 IEEE 35th International Conference on Data Engineering (ICDE), 530-541, 2019 | 30 | 2019 |
| Explaining natural language query results D Deutch, N Frost, A Gilad The VLDB Journal 29 (1), 485-508, 2020 | 29 | 2020 |
| Explainable k-means clustering: Theory and practice S Dasgupta, N Frost, M Moshkovitz, C Rashtchian XXAI Workshop. ICML, 2020 | 22 | 2020 |
| Banzhaf values for facts in query answering O Abramovich, D Deutch, N Frost, A Kara, D Olteanu Proceedings of the ACM on Management of Data 2 (3), 1-26, 2024 | 18 | 2024 |
| Explanations for data repair through shapley values D Deutch, N Frost, A Gilad, O Sheffer Proceedings of the 30th ACM International Conference on Information …, 2021 | 17 | 2021 |
| Nlprov: Natural language provenance D Deutch, N Frost, A Gilad Proceedings of the VLDB Endowment 9 (13), 1537-1540, 2016 | 14 | 2016 |
| Shapgraph: An holistic view of explanations through provenance graphs and shapley values S Davidson, D Deutch, N Frost, B Kimelfeld, O Koren, M Monet Proceedings of the 2022 International Conference on Management of Data, 2373 …, 2022 | 13 | 2022 |
| Explaining Missing Query Results in Natural Language. D Deutch, N Frost, A Gilad, T Haimovich, A Bonifati, Y Zhou, MAV Salles, ... EDBT, 427-430, 2020 | 12 | 2020 |
| Nlprovenans: natural language provenance for non-answers D Deutch, N Frost, A Gilad, T Haimovich Proceedings of the VLDB Endowment 11 (12), 1986-1989, 2018 | 11 | 2018 |
| LearnShapley: Learning to predict rankings of facts contribution based on query logs D Arad, D Deutch, N Frost Proceedings of the 31st ACM International Conference on Information …, 2022 | 9 | 2022 |
| Personal insights for altering decisions of tree-based ensembles over time N Boer, D Deutch, N Frost, T Milo Proceedings of the VLDB Endowment 13 (6), 798-811, 2020 | 9 | 2020 |
| Tabee: Tabular embeddings explanations R Copul, N Frost, T Milo, K Razmadze Proceedings of the ACM on Management of Data 2 (1), 1-26, 2024 | 7 | 2024 |
| CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers M Ben-Tov, D Deutch, N Frost, M Sharif 2024 IEEE Symposium on Security and Privacy (SP), 1345-1364, 2024 | 6 | 2024 |
| SmartTriage: A system for personalized patient data capture, documentation generation, and decision support I Valmianski, N Frost, N Sood, Y Wang, B Liu, JJ Zhu, S Karumuri, IM Finn, ... Machine Learning for Health, 75-96, 2021 | 6 | 2021 |
| Just in time: Personal temporal insights for altering model decisions N Boer, D Deutch, N Frost, T Milo 2019 IEEE 35th International Conference on Data Engineering (ICDE), 1988-1991, 2019 | 6 | 2019 |
Daniel DeutchTel Aviv UniversityVerified email at post.tau.ac.il
