20 citations · 51 across the 18 of their papers we have counts for
6 papers · 1 filter
The Consistency of Probabilistic Databases with Independent Cells
Amir Gilad, Aviram Imber, Benny Kimelfeld
A probabilistic database with attribute-level uncertainty consists of relations where cells of some attributes may hold probability distributions rather than deterministic content.…
PreFair: Privately Generating Justifiably Fair Synthetic Data
David Pujol, Amir Gilad, Ashwin Machanavajjhala
When a database is protected by Differential Privacy (DP), its usability is limited in scope. In this scenario, generating a synthetic version of the data that mimics the propertie…
FEDEX: An Explainability Framework for Data Exploration Steps
Daniel Deutch, Amir Gilad, Tova Milo +2
When exploring a new dataset, Data Scientists often apply analysis queries, look for insights in the resulting dataframe, and repeat to apply further queries. We propose in this pa…
DPXPlain: Privately Explaining Aggregate Query Answers
Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala +1
Differential privacy (DP) is the state-of-the-art and rigorous notion of privacy for answering aggregate database queries while preserving the privacy of sensitive information in t…
HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach
Sainyam Galhotra, Amir Gilad, Sudeepa Roy +1
What-if (provisioning for an update to a database) and how-to (how to modify the database to achieve a goal) analyses provide insights to users who wish to examine hypothetical sce…
Understanding Queries by Conditional Instances
Amir Gilad, Zhengjie Miao, Sudeepa Roy +1
A powerful way to understand a complex query is by observing how it operates on data instances. However, specific database instances are not ideal for such observations: they often…