Yuval Moskovitch

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 40

Top Topics

Data Provenance

Multiple Stages

Hypothetical Reasoning

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

Publications

Felix S. Campbell, Alon Silberstein, Julia Stoyanovich, Yuval Moskovitch
Query Refinement for Diverse Top-k Selection. CoRR (2024)
Felix S. Campbell, Alon Silberstein, Julia Stoyanovich, Yuval Moskovitch
Query Refinement for Diverse Top-k Selection. Proc. ACM Manag. Data 2 (3) (2024)
Jinyang Li, Alon Silberstein, Yuval Moskovitch, Julia Stoyanovich, H. V. Jagadish
ERICA: Query Refinement for Diversity Constraint Satisfaction. Proc. VLDB Endow. 16 (12) (2023)
Yuval Moskovitch, Jinyang Li, H. V. Jagadish
Detection of Groups with Biased Representation in Ranking. CoRR (2023)
Jinyang Li, Yuval Moskovitch, H. V. Jagadish
Detection of Groups with Biased Representation in Ranking. ICDE (2023)
Jinyang Li, Yuval Moskovitch, Julia Stoyanovich, H. V. Jagadish
Query Refinement for Diversity Constraint Satisfaction. Proc. VLDB Endow. 17 (2) (2023)
Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi
On Explaining Confounding Bias. ICDE (2023)
Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi
NEXUS: On Explaining Confounding Bias. SIGMOD Conference Companion (2023)
Yuval Moskovitch, Jinyang Li, H. V. Jagadish
Dexer: Detecting and Explaining Biased Representation in Ranking. SIGMOD Conference Companion (2023)
Yin Lin, Brit Youngmann, Yuval Moskovitch, H. V. Jagadish, Tova Milo
OREO: Detection of Cherry-picked Generalizations. Proc. VLDB Endow. 15 (12) (2022)
Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi
On Explaining Confounding Bias. CoRR (2022)
Yuval Moskovitch, Jinyang Li, H. V. Jagadish
Bias analysis and mitigation in data-driven tools using provenance. TaPP (2022)
Yuval Moskovitch, H. V. Jagadish
Reliability at multiple stages in a data analysis pipeline. Commun. ACM 65 (11) (2022)
Jinyang Li, Yuval Moskovitch, H. V. Jagadish
DENOUNCER: Detection of Unfairness in Classifiers. Proc. VLDB Endow. 14 (12) (2021)
Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch
PITA: Privacy Through Provenance Abstraction. ICDE (2021)
Yin Lin, Brit Youngmann, Yuval Moskovitch, H. V. Jagadish, Tova Milo
On Detecting Cherry-picked Generalizations. Proc. VLDB Endow. 15 (1) (2021)
Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch
On Optimizing the Trade-off between Privacy and Utility in Data Provenance. SIGMOD Conference (2021)
Yuval Moskovitch, H. V. Jagadish
Patterns Count-Based Labels for Datasets. ICDE (2021)
Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch
On Optimizing the Trade-off between Privacy and Utility in Data Provenance. CoRR (2021)
Amir Gilad, Yuval Moskovitch
Towards Inferring Queries from Simple and Partial Provenance Examples. CoRR (2020)
Pierre Bourhis, Daniel Deutch, Yuval Moskovitch
Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. CoRR (2020)
Yuval Moskovitch, H. V. Jagadish
Patterns Count-Based Labels for Datasets. CoRR (2020)
Pierre Bourhis, Daniel Deutch, Yuval Moskovitch
Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. SIGMOD Conference (2020)
Daniel Deutch, Yuval Moskovitch, Noam Rinetzky
COBRA: Compression via Abstraction of Provenance for Hypothetical Reasoning. CoRR (2020)
Tova Milo, Yuval Moskovitch, Brit Youngmann
Contribution Maximization in Probabilistic Datalog. ICDE (2020)
Daniel Deutch, Yuval Moskovitch, Noam Rinetzky
Hypothetical Reasoning via Provenance Abstraction. CoRR (2020)
Yuval Moskovitch, H. V. Jagadish
COUNTATA: Dataset Labeling Using Pattern Counts. Proc. VLDB Endow. 13 (12) (2020)
Amir Gilad, Yuval Moskovitch
Towards Inferring Queries from Simple and Partial Provenance Examples. CIKM (2020)
Tova Milo, Yuval Moskovitch, Brit Youngmann
PODIUM: Probabilistic Datalog Analysis via Contribution Maximization. CIKM (2019)
Daniel Deutch, Evgeny Marants, Yuval Moskovitch
Datalignment: Ontology Schema Alignment Through Datalog Containment. Proc. VLDB Endow. 12 (12) (2019)
Daniel Deutch, Yuval Moskovitch, Noam Rinetzky
Hypothetical Reasoning via Provenance Abstraction. SIGMOD Conference (2019)
Daniel Deutch, Yuval Moskovitch, Noam Rinetzky
COBRA: Compression Via Abstraction of Provenance for Hypothetical Reasoning. ICDE (2019)
Daniel Deutch, Amir Gilad, Yuval Moskovitch
Efficient provenance tracking for datalog using top-k queries. VLDB J. 27 (2) (2018)
Daniel Deutch, Yuval Moskovitch, Itay Polak, Noam Rinetzky
Towards Hypothetical Reasoning Using Distributed Provenance. EDBT (2018)
Pierre Bourhis, Daniel Deutch, Yuval Moskovitch
POLYTICS: Provenance-Based Analytics of Data-Centric Applications. ICDE (2017)
Pierre Bourhis, Daniel Deutch, Yuval Moskovitch
Analyzing data-centric applications: Why, what-if, and how-to. ICDE (2016)
Daniel Deutch, Amir Gilad, Yuval Moskovitch
Towards web-scale how-provenance. ICDE Workshops (2015)
Daniel Deutch, Amir Gilad, Yuval Moskovitch
selP: Selective tracking and presentation of data provenance. ICDE (2015)
Daniel Deutch, Yuval Moskovitch, Val Tannen
Provenance-based analysis of data-centric processes. VLDB J. 24 (4) (2015)
Daniel Deutch, Amir Gilad, Yuval Moskovitch
Selective Provenance for Datalog Programs Using Top-K Queries. Proc. VLDB Endow. 8 (12) (2015)
Daniel Deutch, Yuval Moskovitch, Val Tannen
A Provenance Framework for Data-Dependent Process Analysis. Proc. VLDB Endow. 7 (6) (2014)
Daniel Deutch, Yuval Moskovitch, Val Tannen
PROPOLIS: Provisioned Analysis of Data-Centric Processes. Proc. VLDB Endow. 6 (12) (2013)