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Nave Frost
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2020 – today
- 2025
- [i10]Matan Ben-Tov, Daniel Deutch, Nave Frost, Mahmood Sharif:
CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers. CoRR abs/2501.10013 (2025) - 2024
- [j10]Roni Copul
, Nave Frost
TabEE: Tabular Embeddings Explanations. Proc. ACM Manag. Data 2(1): 72:1-72:26 (2024) - [j9]Omer Abramovich
Banzhaf Values for Facts in Query Answering. Proc. ACM Manag. Data 2(3): 123 (2024) - [j8]Roni Copul, Nave Frost, Tova Milo, Kathy Razmadze:
Demonstrating TabEE: Tabular Embedding Explanations. Proc. VLDB Endow. 17(12): 4285-4288 (2024) - [c17]Nave Frost, Zachary C. Lipton, Yishay Mansour, Michal Moshkovitz:
Partially Interpretable Models with Guarantees on Coverage and Accuracy. ALT 2024: 590-613 - [c16]Aviv Ben-Arie, Daniel Deutch, Nave Frost, Yair Horesh, Idan Meyuhas:
Optimizing Counterfactual-based Analysis of Machine Learning Models Through Databases. EDBT 2024: 597-609 - [c15]Dana Arad, Daniel Deutch, Nave Frost:
Predicting Fact Contributions from Query Logs with Machine Learning. EDBT 2024: 704-716 - [c14]Matan Ben-Tov, Daniel Deutch, Nave Frost, Mahmood Sharif:
CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers. SP 2024: 1345-1364 - 2023
- [i9]Omer Abramovich, Daniel Deutch, Nave Frost, Ahmet Kara
Banzhaf Values for Facts in Query Answering. CoRR abs/2308.05588 (2023) - 2022
- [b1]Nave Frost:
Toward Explainable Data Science. Tel Aviv University, Israel, 2022 - [c13]Dana Arad, Daniel Deutch, Nave Frost:
LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs. CIKM 2022: 4788-4792 - [c12]Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz:
Framework for Evaluating Faithfulness of Local Explanations. ICML 2022: 4794-4815 - [c11]Daniel Deutch, Nave Frost, Benny Kimelfeld, Mikaël Monet:
Computing the Shapley Value of Facts in Query Answering. SIGMOD Conference 2022: 1570-1583 - [c10]Susan B. Davidson, Daniel Deutch, Nave Frost, Benny Kimelfeld, Omer Koren, Mikaël Monet:
ShapGraph: An Holistic View of Explanations through Provenance Graphs and Shapley Values. SIGMOD Conference 2022: 2373-2376 - [i8]Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz:
Framework for Evaluating Faithfulness of Local Explanations. CoRR abs/2202.00734 (2022) - 2021
- [c9]Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer:
Explanations for Data Repair Through Shapley Values. CIKM 2021: 362-371 - [c8]Ilya Valmianski, Nave Frost, Navdeep Sood, Yang Wang, Baodong Liu, James J. Zhu, Sunil Karumuri, Ian M. Finn, Daniel S. Zisook:
SmartTriage: A system for personalized patient data capture, documentation generation, and decision support. ML4H@NeurIPS 2021: 75-96 - [i7]Daniel Deutch, Nave Frost, Benny Kimelfeld, Mikaël Monet:
Computing the Shapley Value of Facts in Query Answering. CoRR abs/2112.08874 (2021) - 2020
- [j7]Nave Frost, Naama Boer, Daniel Deutch, Tova Milo:
Personal Insights for Altering Decisions of Tree-based Ensembles over Time. Proc. VLDB Endow. 13(6): 798-811 (2020) - [j6]Daniel Deutch, Nave Frost, Amir Gilad
Explaining Natural Language query results. VLDB J. 29(1): 485-508 (2020) - [c7]Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich:
Explaining Missing Query Results in Natural Language. EDBT 2020: 427-430 - [c6]Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost:
Explainable k-Means and k-Medians Clustering. ICML 2020: 7055-7065 - [c5]Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer:
T-REx: Table Repair Explanations. SIGMOD Conference 2020: 2765-2768 - [i6]Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz, Cyrus Rashtchian:
Explainable k-Means and k-Medians Clustering. CoRR abs/2002.12538 (2020) - [i5]Nave Frost, Michal Moshkovitz, Cyrus Rashtchian:
ExKMC: Expanding Explainable k-Means Clustering. CoRR abs/2006.02399 (2020) - [i4]Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer:
T-REx: Table Repair Explanations. CoRR abs/2007.04450 (2020) - [i3]Naama Boer, Daniel Deutch, Nave Frost, Tova Milo:
Just in Time: Personal Temporal Insights for Altering Model Decisions. CoRR abs/2007.04453 (2020) - [i2]Daniel Deutch, Nave Frost, Amir Gilad:
Explaining Natural Language Query Results. CoRR abs/2007.04454 (2020) - [i1]Ilya Valmianski, Ian M. Finn, Nave Frost, Yang Wang, Baodong Liu, James J. Zhu, Sunil Karumuri, Daniel S. Zisook:
SmartTriage: A system for personalized patient data capture, documentation generation, and decision support. CoRR abs/2010.09905 (2020)
2010 – 2019
- 2019
- [c4]Daniel Deutch, Nave Frost:
Constraints-Based Explanations of Classifications. ICDE 2019: 530-541 - [c3]Naama Boer, Daniel Deutch, Nave Frost, Tova Milo:
Just in Time: Personal Temporal Insights for Altering Model Decisions. ICDE 2019: 1988-1991 - [c2]Nave Frost:
Explaining Results of Data-Driven Applications. ICDE 2019: 2081-2085 - 2018
- [j5]Daniel Deutch, Nave Frost, Amir Gilad:
Provenance for Non-Experts. IEEE Data Eng. Bull. 41(1): 3-14 (2018) - [j4]Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich:
NLProveNAns: Natural Language Provenance for Non-Answers. Proc. VLDB Endow. 11(12): 1986-1989 (2018) - [j3]Daniel Deutch, Nave Frost, Amir Gilad:
Natural Language Explanations for Query Results. SIGMOD Rec. 47(1): 42-49 (2018) - [c1]Daniel Deutch, Nave Frost:
CEC: Constraints based Explanation for Classifications. CIKM 2018: 1879-1882 - 2017
- [j2]Daniel Deutch, Nave Frost, Amir Gilad:
Provenance for Natural Language Queries. Proc. VLDB Endow. 10(5): 577-588 (2017) - 2016
- [j1]Daniel Deutch, Nave Frost, Amir Gilad:
NLProv: Natural Language Provenance. Proc. VLDB Endow. 9(13): 1537-1540 (2016)
Coauthor Index
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last updated on 2025-03-11 20:01 CET by the dblp team
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