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Daniel Deutch
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2020 – today
- 2024
- [j36]Omer Abramovich
, Daniel Deutch
Banzhaf Values for Facts in Query Answering. Proc. ACM Manag. Data 2(3): 123 (2024) - [c61]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 - [c60]Dana Arad, Daniel Deutch, Nave Frost:
Predicting Fact Contributions from Query Logs with Machine Learning. EDBT 2024: 704-716 - [c59]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
- [c58]Ori Yoran, Tomer Wolfson, Ben Bogin, Uri Katz
Answering Questions by Meta-Reasoning over Multiple Chains of Thought. EMNLP 2023: 5942-5966 - [i21]Ori Yoran, Tomer Wolfson, Ben Bogin, Uri Katz, Daniel Deutch, Jonathan Berant:
Answering Questions by Meta-Reasoning over Multiple Chains of Thought. CoRR abs/2304.13007 (2023) - [i20]Omer Abramovich, Daniel Deutch, Nave Frost, Ahmet Kara
Banzhaf Values for Facts in Query Answering. CoRR abs/2308.05588 (2023) - 2022
- [j35]Daniel Deutch, Amir Gilad, Tova Milo, Amit Mualem, Amit Somech
FEDEX: An Explainability Framework for Data Exploration Steps. Proc. VLDB Endow. 15(13): 3854-3868 (2022) - [c57]Dana Arad, Daniel Deutch, Nave Frost:
LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs. CIKM 2022: 4788-4792 - [c56]Amit Bergman, Viviane Slon, Daniel Deutch:
exML: An Explainable Maximum Likelihood Tool for Proportion Estimation in DNA Data. CIKM 2022: 4818-4822 - [c55]Tomer Wolfson, Daniel Deutch, Jonathan Berant:
Weakly Supervised Text-to-SQL Parsing through Question Decomposition. NAACL-HLT (Findings) 2022: 2528-2542 - [c54]Daniel Deutch, Nave Frost, Benny Kimelfeld, Mikaël Monet:
Computing the Shapley Value of Facts in Query Answering. SIGMOD Conference 2022: 1570-1583 - [c53]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 - [c52]Idan Meyuhas, Aviv Ben-Arie, Yair Horesh
CFDB: Machine Learning Model Analysis via Databases of CounterFactuals. SIGMOD Conference 2022: 2401-2404 - [c51]Daniel Deutch, Tanu Malik, Adriane Chapman:
Theory and Practice of Provenance. SIGMOD Conference 2022: 2544-2545 - [e1]Adriane Chapman, Daniel Deutch, Tanu Malik:
Proceedings of the 14th International Workshop on the Theory and Practice of Provenance, TaPP 2022, Philadelphia, Pennsylvania, 17 June 2022. ACM 2022, ISBN 978-1-4503-9349-2 [contents] - [i19]Daniel Deutch, Amir Gilad, Tova Milo, Amit Mualem, Amit Somech:
FEDEX: An Explainability Framework for Data Exploration Steps. CoRR abs/2209.06260 (2022) - 2021
- [c50]Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer:
Explanations for Data Repair Through Shapley Values. CIKM 2021: 362-371 - [c49]Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch:
PITA: Privacy Through Provenance Abstraction. ICDE 2021: 2713-2716 - [c48]Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch:
On Optimizing the Trade-off between Privacy and Utility in Data Provenance. SIGMOD Conference 2021: 379-391 - [i18]Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch:
On Optimizing the Trade-off between Privacy and Utility in Data Provenance. CoRR abs/2103.00288 (2021) - [i17]Tomer Wolfson, Jonathan Berant, Daniel Deutch:
Weakly Supervised Mapping of Natural Language to SQL through Question Decomposition. CoRR abs/2112.06311 (2021) - [i16]Daniel Deutch, Nave Frost, Benny Kimelfeld, Mikaël Monet:
Computing the Shapley Value of Facts in Query Answering. CoRR abs/2112.08874 (2021) - 2020
- [j34]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) - [j33]Daniel Deutch, Amir Gilad, Tova Milo, Amit Somech
ExplainED: Explanations for EDA Notebooks. Proc. VLDB Endow. 13(12): 2917-2920 (2020) - [j32]Amir Gilad, Yihao Hu, Daniel Deutch, Sudeepa Roy:
MuSe: Multiple Deletion Semantics for Data Repair. Proc. VLDB Endow. 13(12): 2921-2924 (2020) - [j31]Tomer Wolfson, Mor Geva
Break It Down: A Question Understanding Benchmark. Trans. Assoc. Comput. Linguistics 8: 183-198 (2020) - [j30]Daniel Deutch, Nave Frost, Amir Gilad
Explaining Natural Language query results. VLDB J. 29(1): 485-508 (2020) - [c47]Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich:
Explaining Missing Query Results in Natural Language. EDBT 2020: 427-430 - [c46]Pierre Bourhis, Daniel Deutch, Yuval Moskovitch:
Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. SIGMOD Conference 2020: 415-429 - [c45]Amir Gilad, Daniel Deutch, Sudeepa Roy:
On Multiple Semantics for Declarative Database Repairs. SIGMOD Conference 2020: 817-831 - [c44]Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer:
T-REx: Table Repair Explanations. SIGMOD Conference 2020: 2765-2768 - [i15]Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch, Jonathan Berant:
Break It Down: A Question Understanding Benchmark. CoRR abs/2001.11770 (2020) - [i14]Amir Gilad, Daniel Deutch, Sudeepa Roy:
On Multiple Semantics for Declarative Database Repairs. CoRR abs/2004.05065 (2020) - [i13]Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer:
T-REx: Table Repair Explanations. CoRR abs/2007.04450 (2020) - [i12]Naama Boer, Daniel Deutch, Nave Frost, Tova Milo:
Just in Time: Personal Temporal Insights for Altering Model Decisions. CoRR abs/2007.04453 (2020) - [i11]Daniel Deutch, Nave Frost, Amir Gilad:
Explaining Natural Language Query Results. CoRR abs/2007.04454 (2020) - [i10]Daniel Deutch, Yuval Moskovitch, Noam Rinetzky:
COBRA: Compression via Abstraction of Provenance for Hypothetical Reasoning. CoRR abs/2007.05389 (2020) - [i9]Daniel Deutch, Yuval Moskovitch, Noam Rinetzky:
Hypothetical Reasoning via Provenance Abstraction. CoRR abs/2007.05400 (2020) - [i8]Pierre Bourhis, Daniel Deutch, Yuval Moskovitch:
Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. CoRR abs/2007.05463 (2020)
2010 – 2019
- 2019
- [j29]Yinjun Wu, Abdussalam Alawini, Daniel Deutch, Tova Milo, Susan B. Davidson:
ProvCite: Provenance-based Data Citation. Proc. VLDB Endow. 12(7): 738-751 (2019) - [j28]Daniel Deutch, Evgeny Marants, Yuval Moskovitch:
Datalignment: Ontology Schema Alignment Through Datalog Containment. Proc. VLDB Endow. 12(12): 1870-1873 (2019) - [j27]Antoine Amarilli, Mouhamadou Lamine Ba, Daniel Deutch, Pierre Senellart:
Computing possible and certain answers over order-incomplete data. Theor. Comput. Sci. 797: 42-76 (2019) - [c43]Daniel Deutch, Amir Gilad:
Reverse-Engineering Conjunctive Queries from Provenance Examples. EDBT 2019: 277-288 - [c42]Daniel Deutch, Nave Frost:
Constraints-Based Explanations of Classifications. ICDE 2019: 530-541 - [c41]Jonathan Berant, Daniel Deutch, Amir Globerson, Tova Milo, Tomer Wolfson:
Explaining Queries Over Web Tables to Non-experts. ICDE 2019: 1570-1573 - [c40]Naama Boer, Daniel Deutch, Nave Frost, Tova Milo:
Just in Time: Personal Temporal Insights for Altering Model Decisions. ICDE 2019: 1988-1991 - [c39]Daniel Deutch, Yuval Moskovitch, Noam Rinetzky:
COBRA: Compression Via Abstraction of Provenance for Hypothetical Reasoning. ICDE 2019: 2016-2019 - [c38]Daniel Deutch, Yuval Moskovitch, Noam Rinetzky:
Hypothetical Reasoning via Provenance Abstraction. SIGMOD Conference 2019: 537-554 - 2018
- [j26]Daniel Deutch, Nave Frost, Amir Gilad:
Provenance for Non-Experts. IEEE Data Eng. Bull. 41(1): 3-14 (2018) - [j25]Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich:
NLProveNAns: Natural Language Provenance for Non-Answers. Proc. VLDB Endow. 11(12): 1986-1989 (2018) - [j24]Efrat Abramovitz, Daniel Deutch, Amir Gilad:
QuestPro: Queries in SPARQL Through Provenance. Proc. VLDB Endow. 11(12): 1994-1997 (2018) - [j23]Daniel Deutch, Nave Frost, Amir Gilad:
Natural Language Explanations for Query Results. SIGMOD Rec. 47(1): 42-49 (2018) - [j22]Daniel Deutch, Amir Gilad
Efficient provenance tracking for datalog using top-k queries. VLDB J. 27(2): 245-269 (2018) - [c37]Daniel Deutch, Nave Frost:
CEC: Constraints based Explanation for Classifications. CIKM 2018: 1879-1882 - [c36]Daniel Deutch, Yehonatan Ginzberg, Tova Milo:
Preserving Privacy of Fraud Detection Rule Sharing Using Intel's SGX. CIKM 2018: 1935-1938 - [c35]Daniel Deutch, Yuval Moskovitch, Itay Polak, Noam Rinetzky:
Towards Hypothetical Reasoning Using Distributed Provenance. EDBT 2018: 461-464 - [c34]Efrat Abramovitz, Daniel Deutch, Amir Gilad:
Interactive Inference of SPARQL Queries Using Provenance. ICDE 2018: 581-592 - [i7]Antoine Amarilli, Mouhamadou Lamine Ba, Daniel Deutch, Pierre Senellart:
Computing Possible and Certain Answers over Order-Incomplete Data. CoRR abs/1801.06396 (2018) - [i6]Jonathan Berant, Daniel Deutch, Amir Globerson, Tova Milo, Tomer Wolfson:
Explaining Queries over Web Tables to Non-Experts. CoRR abs/1808.04614 (2018) - 2017
- [j21]Daniel Deutch, Nave Frost, Amir Gilad:
Provenance for Natural Language Queries. Proc. VLDB Endow. 10(5): 577-588 (2017) - [c33]Susan B. Davidson, Daniel Deutch, Tova Milo, Gianmaria Silvello:
A Model for Fine-Grained Data Citation. CIDR 2017 - [c32]Pierre Bourhis, Daniel Deutch, Yuval Moskovitch:
POLYTICS: Provenance-Based Analytics of Data-Centric Applications. ICDE 2017: 1373-1374 - [c31]Susan B. Davidson, Peter Buneman, Daniel Deutch, Tova Milo, Gianmaria Silvello
Data Citation: A Computational Challenge. PODS 2017: 1-4 - [c30]Susan B. Davidson, Daniel Deutch, Tova Milo, Gianmaria Silvello:
A Model for Fine-Grained Data Citation. SEBD 2017: 17 - [c29]Antoine Amarilli, Mouhamadou Lamine Ba, Daniel Deutch, Pierre Senellart
Possible and Certain Answers for Queries over Order-Incomplete Data. TIME 2017: 4:1-4:19 - [i5]Antoine Amarilli, Mouhamadou Lamine Ba, Daniel Deutch, Pierre Senellart:
Possible and Certain Answers for Queries over Order-Incomplete Data. CoRR abs/1707.07222 (2017) - 2016
- [j20]Daniel Deutch, Nave Frost, Amir Gilad:
NLProv: Natural Language Provenance. Proc. VLDB Endow. 9(13): 1537-1540 (2016) - [c28]Eleanor Ainy, Pierre Bourhis, Susan B. Davidson, Daniel Deutch, Tova Milo:
PROX: Approximated Summarization of Data Provenance. EDBT 2016: 620-623 - [c27]Pierre Bourhis, Daniel Deutch, Yuval Moskovitch:
Analyzing data-centric applications: Why, what-if, and how-to. ICDE 2016: 779-790 - [c26]Daniel Deutch, Amir Gilad:
QPlain: Query by explanation. ICDE 2016: 1358-1361 - [i4]Daniel Deutch, Amir Gilad:
Learning Queries from Examples and Their Explanations. CoRR abs/1602.03819 (2016) - 2015
- [j19]Serge Abiteboul, Yael Amsterdamer
Optimal Probabilistic Generation of XML Documents. Theory Comput. Syst. 57(4): 806-842 (2015) - [j18]Daniel Deutch, Amir Gilad, Yuval Moskovitch:
Selective Provenance for Datalog Programs Using Top-K Queries. Proc. VLDB Endow. 8(12): 1394-1405 (2015) - [j17]Daniel Deutch, Yuval Moskovitch, Val Tannen:
Provenance-based analysis of data-centric processes. VLDB J. 24(4): 583-607 (2015) - [c25]Eleanor Ainy, Pierre Bourhis, Susan B. Davidson, Daniel Deutch, Tova Milo:
Approximated Summarization of Data Provenance. CIKM 2015: 483-492 - [c24]Daniel Deutch, Amir Gilad, Yuval Moskovitch:
Towards web-scale how-provenance. ICDE Workshops 2015: 68-70 - [c23]Daniel Deutch, Amir Gilad, Yuval Moskovitch:
selP: Selective tracking and presentation of data provenance. ICDE 2015: 1484-1487 - 2014
- [j16]Daniel Deutch, Yuval Moskovitch, Val Tannen:
A Provenance Framework for Data-Dependent Process Analysis. Proc. VLDB Endow. 7(6): 457-468 (2014) - [c22]Serge Abiteboul, Daniel Deutch, Victor Vianu:
Deduction with Contradictions in Datalog. ICDT 2014: 143-154 - [c21]Daniel Deutch, Tova Milo, Sudeepa Roy, Val Tannen:
Circuits for Datalog Provenance. ICDT 2014: 201-212 - [c20]Eleanor Ainy, Susan B. Davidson, Daniel Deutch, Tova Milo:
Approximated Provenance for Complex Applications. TAPP 2014 - 2013
- [j15]Daniel Deutch:
Querying Probabilistic Business Processes for Sub-Flows. Theory Comput. Syst. 52(3): 367-402 (2013) - [j14]Daniel Deutch, Yuval Moskovitch, Val Tannen:
PROPOLIS: Provisioned Analysis of Data-Centric Processes. Proc. VLDB Endow. 6(12): 1302-1305 (2013) - [j13]Daniel Deutch, Tova Milo, Neoklis Polyzotis:
Top-k queries over web applications. VLDB J. 22(4): 519-542 (2013) - [c19]Daniel Deutch, Zachary G. Ives, Tova Milo, Val Tannen:
Caravan: Provisioning for What-If Analysis. CIDR 2013 - 2012
- [b2]Daniel Deutch, Tova Milo:
Business Processes: A Database Perspective. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2012, ISBN 978-3-031-00763-7 - [j12]Daniel Deutch, Tova Milo:
A structural/temporal query language for Business Processes. J. Comput. Syst. Sci. 78(2): 583-609 (2012) - [j11]Yael Amsterdamer
On Provenance Minimization. ACM Trans. Database Syst. 37(4): 30:1-30:36 (2012) - [j10]Daniel Deutch, Tova Milo:
Type inference and type checking for queries over execution traces. VLDB J. 21(1): 51-68 (2012) - [c18]Serge Abiteboul, Yael Amsterdamer
Finding optimal probabilistic generators for XML collections. ICDT 2012: 127-139 - [c17]Meghyn Bienvenu, Daniel Deutch, Fabian M. Suchanek:
Provenance for Web 2.0 Data. Secure Data Management 2012: 148-155 - [c16]Daniel Deutch, Tova Milo:
Mob data sourcing. SIGMOD Conference 2012: 581-584 - [c15]Meghyn Bienvenu, Daniel Deutch, Davide Martinenghi, Pierre Senellart, Fabian M. Suchanek:
Dealing with the Deep Web and all its Quirks. VLDS 2012: 21-24 - [c14]Serge Abiteboul, Meghyn Bienvenu, Daniel Deutch:
Deduction in the Presence of Distribution and Contradictions. WebDB 2012: 31-36 - [c13]Daniel Deutch, Ohad Greenshpan, Boris Kostenko, Tova Milo:
Declarative platform for data sourcing games. WWW 2012: 779-788 - [i3]Yael Amsterdamer, Susan B. Davidson, Daniel Deutch, Tova Milo, Julia Stoyanovich, Val Tannen:
Putting Lipstick on Pig: Enabling Database-style Workflow Provenance. CoRR abs/1201.0231 (2012) - 2011
- [j9]Yael Amsterdamer
Putting Lipstick on Pig: Enabling Database-style Workflow Provenance. Proc. VLDB Endow. 5(4): 346-357 (2011) - [c12]Daniel Deutch, Ohad Greenshpan, Boris Kostenko, Tova Milo:
Using Markov Chain Monte Carlo to play Trivia. ICDE 2011: 1308-1311 - [c11]Daniel Deutch:
Querying probabilistic business processes for sub-flows. ICDT 2011: 54-65 - [c10]Daniel Deutch, Tova Milo:
A quest for beauty and wealth (or, business processes for database researchers). PODS 2011: 1-12 - [c9]Yael Amsterdamer
On provenance minimization. PODS 2011: 141-152 - [c8]Yael Amsterdamer
Provenance for aggregate queries. PODS 2011: 153-164 - [c7]Yael Amsterdamer
On the Limitations of Provenance for Queries with Difference. TaPP 2011 - [c6]Yael Amsterdamer
On the optimality of top-k algorithms for Interactive Web Applications. WebDB 2011 - [i2]Yael Amsterdamer, Daniel Deutch, Val Tannen:
Provenance for Aggregate Queries. CoRR abs/1101.1110 (2011) - [i1]Yael Amsterdamer, Daniel Deutch, Val Tannen:
On the Limitations of Provenance for Queries With Difference. CoRR abs/1105.2255 (2011) - 2010
- [b1]Daniel Deutch:
Querying web-based applications under models of uncertainty. Tel Aviv University, Israel, 2010 - [j8]Daniel Deutch, Ohad Greenshpan, Tova Milo:
Navigating in Complex Mashed-Up Applications. Proc. VLDB Endow. 3(1): 320-329 (2010) - [j7]Daniel Deutch, Tova Milo, Neoklis Polyzotis, Tom Yam:
Optimal Top-K Query Evaluation for Weighted Business Processes. Proc. VLDB Endow. 3(1): 940-951 (2010) - [j6]Daniel Deutch, Tova Milo:
On models and query languages for probabilistic processes. SIGMOD Rec. 39(2): 27-38 (2010) - [c5]Daniel Deutch, Ohad Greenshpan, Tova Milo:
Navigating through Mashed-up Applications with COMPASS. ICDE 2010: 1117-1120 - [c4]Daniel Deutch, Christoph Koch, Tova Milo:
On probabilistic fixpoint and Markov chain query languages. PODS 2010: 215-226
2000 – 2009
- 2009
- [j5]Daniel Deutch, Tova Milo:
Querying Future and Past in Business Processes. IEEE Data Eng. Bull. 32(3): 29-34 (2009) - [j4]Daniel Deutch, Tova Milo, Tom Yam:
Goal-Oriented Web-site Navigation for On-line Shoppers. Proc. VLDB Endow. 2(2): 1642-1645 (2009) - [c3]Daniel Deutch, Tova Milo:
Evaluating TOP-K Queries over Business Processes. ICDE 2009: 1195-1198 - [c2]Daniel Deutch, Tova Milo:
TOP-K projection queries for probabilistic business processes. ICDT 2009: 239-251 - 2008
- [j3]Daniel Deutch, Tova Milo:
Type inference and type checking for queries on execution traces. Proc. VLDB Endow. 1(1): 352-363 (2008) - [j2]Tova Milo, Daniel Deutch:
Querying and monitoring distributed business processes. Proc. VLDB Endow. 1(2): 1512-1515 (2008) - [j1]Daniel Deutch, Tova Milo:
Querying web-based applications under models of uncertainty. Proc. VLDB Endow. 1(2): 1659-1665 (2008) - 2007
- [c1]Daniel Deutch, Tova Milo:
Querying Structural and Behavioral Properties of Business Processes. DBPL 2007: 169-185
Coauthor Index
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last updated on 2024-10-07 21:16 CEST by the dblp team
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