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20102024
most citedDPXPlain: Privately Explaining Aggregate Query Answers

1 citations · 2 across the 5 of their papers we have counts for

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cs.DB2024

Qr-Hint: Actionable Hints Towards Correcting Wrong SQL Queries

Yihao Hu, Amir Gilad, Kristin Stephens-Martinez +2

We describe a system called Qr-Hint that, given a (correct) target query Q* and a (wrong) working query Q, both expressed in SQL, provides actionable hints for the user to fix the…

cs.DB20241 cited

Evaluating Datalog over Semirings: A Grounding-based Approach

Hangdong Zhao, Shaleen Deep, Paraschos Koutris +2

Datalog is a powerful yet elegant language that allows expressing recursive computation. Although Datalog evaluation has been extensively studied in the literature, so far, only lo…

cs.DB2023

DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms

Shweta Patwa, Danyu Sun, Amir Gilad +2

Synthetic data generation methods, and in particular, private synthetic data generation methods, are gaining popularity as a means to make copies of sensitive databases that can be…

cs.DB20221 cited

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…

cs.DB2010

Provenance Views for Module Privacy

Susan B. Davidson, Sanjeev Khanna, Tova Milo +2

Scientific workflow systems increasingly store provenance information about the module executions used to produce a data item, as well as the parameter settings and intermediate da…