2 citations · 4 across the 12 of their papers we have counts for
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Patterns Count-Based Labels for Datasets
Yuval Moskovitch, H. V. Jagadish
Counts of attribute-value combinations are central to the profiling of a dataset, particularly in determining fitness for use and in eliminating bias and unfairness. While counts o…
Towards Inferring Queries from Simple and Partial Provenance Examples
Amir Gilad, Yuval Moskovitch
The field of query-by-example aims at inferring queries from output examples given by non-expert users, by finding the underlying logic that binds the examples. However, for a very…
Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries
Pierre Bourhis, Daniel Deutch, Yuval Moskovitch
The algebraic approach for provenance tracking, originating in the semiring model of Green et. al, has proven useful as an abstract way of handling metadata. Commutative Semirings…
Hypothetical Reasoning via Provenance Abstraction
Daniel Deutch, Yuval Moskovitch, Noam Rinetzky
Data analytics often involves hypothetical reasoning: repeatedly modifying the data and observing the induced effect on the computation result of a data-centric application. Previo…
COBRA: Compression via Abstraction of Provenance for Hypothetical Reasoning
Daniel Deutch, Yuval Moskovitch, Noam Rinetzky
Data analytics often involves hypothetical reasoning: repeatedly modifying the data and observing the induced effect on the computation result of a data-centric application. Recent…