Amir Gilad

According to our database, Amir Gilad authored at least 56 papers between 2015 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

CoDeC: Constraints-Guided Diverse Counterfactuals.

Avia Asael, Nave Frost, Amir Gilad, Daniel Deutch

Proceedings of the Proceedings 29th International Conference on Extending Database Technology, 2026

2025

Analyzing Deviations from Monotonic Trends through Database Repair.

Shunit Agmon, Jonathan Gal, Amir Gilad, Ester Livshits, Or Mutay, Brit Youngmann, Benny Kimelfeld

CoRR, December, 2025

ClaimIt: Finding Convincing Views to Endorse a Claim.

Shunit Agmon, David Avigdor, Brit Youngmann, Amir Gilad, Benny Kimelfeld

Proc. VLDB Endow., August, 2025

Computing Inconsistency Measures Under Differential Privacy.

Shubhankar Mohapatra, Amir Gilad, Xi He, Benny Kimelfeld

Proc. ACM Manag. Data, June, 2025

Differentially private explanations for aggregate query answers.

Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy

VLDB J., March, 2025

Differentially Private Explanations for Clusters.

Amir Gilad, Tova Milo, Kathy Razmadze, Ron Zadicario

Proc. ACM Manag. Data, 2025

Advancing causal inference in medicine using biobank data.

Hadasa Kaufman, Nadav Rappoport, Amir Gilad, Michal Linial

J. Biomed. Informatics, 2025

CauSumX: Summarized Causal Explanations For Group-By-Average Queries.

Nativ Levy, Michael J. Cafarella, Amir Gilad, Sudeepa Roy, Brit Youngmann

Proceedings of the Companion of the 2025 International Conference on Management of Data, 2025

Demonstration of DPClustX: Differentially Private Explanations for Clusters.

Amir Gilad, Tova Milo, Kathy Razmadze, Ron Zadicario

Proceedings of the Companion of the 2025 International Conference on Management of Data, 2025

Refining Labeling Functions with Limited Labeled Data.

Chenjie Li, Amir Gilad, Boris Glavic, Zhengjie Miao, Sudeepa Roy

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2024

The Cost of Representation by Subset Repairs.

Yuxi Liu, Fangzhu Shen, Kushagra Ghosh, Amir Gilad, Benny Kimelfeld, Sudeepa Roy

Proc. VLDB Endow., October, 2024

Finding Convincing Views to Endorse a Claim.

Shunit Agmon, Amir Gilad, Brit Youngmann, Shahar Zoarets, Benny Kimelfeld

Proc. VLDB Endow., October, 2024

PD-Explain: A Unified Python-native Framework for Query Explanations Over DataFrames.

Itay Elyashiv, Amir Gilad, Edna Isakov, Tal Tikochinsky, Amit Somech

Proc. VLDB Endow., August, 2024

Summarized Causal Explanations For Aggregate Views.

Brit Youngmann, Michael J. Cafarella, Amir Gilad, Sudeepa Roy

Proc. ACM Manag. Data, February, 2024

Qr-Hint: Actionable Hints Towards Correcting Wrong SQL Queries.

Yihao Hu, Amir Gilad, Kristin Stephens-Martinez, Sudeepa Roy, Jun Yang

Proc. ACM Manag. Data, 2024

Summarized Causal Explanations For Aggregate Views (Full version).

Brit Youngmann, Michael J. Cafarella, Amir Gilad, Sudeepa Roy

CoRR, 2024

First Workshop on Governance, Understanding and Integration of Data for Effective and Responsible AI (GUIDE-AI).

Abolfazl Asudeh, Sainyam Galhotra, Amir Gilad, Babak Salimi, Brit Youngmann

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk).

Sudeepa Roy, Amir Gilad, Yihao Hu, Hanze Meng, Zhengjie Miao, Kristin Stephens-Martinez, Jun Yang

Proceedings of the 27th International Conference on Database Theory, 2024

What Teaching Databases Taught Us about Researching Databases: Extended Talk Abstract.

Jun Yang, Amir Gilad, Yihao Hu, Hanze Meng, Zhengjie Miao, Sudeepa Roy, Kristin Stephens-Martinez

Proceedings of the 3rd International Workshop on Data Systems Education: Bridging education practice with education research, 2024

2023

Explaining Differentially Private Query Results With DPXPlain.

Tingyu Wang, Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy

Proc. VLDB Endow., 2023

PreFair: Privately Generating Justifiably Fair Synthetic Data.

David Pujol, Amir Gilad, Ashwin Machanavajjhala

Proc. VLDB Endow., 2023

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

Shweta Patwa, Danyu Sun, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy

Proc. VLDB Endow., 2023

Characterizing and Verifying Queries Via CINSGEN.

Hanze Meng, Zhengjie Miao, Amir Gilad, Sudeepa Roy, Jun Yang

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

The Consistency of Probabilistic Databases with Independent Cells.

Amir Gilad, Aviram Imber, Benny Kimelfeld

Proceedings of the 26th International Conference on Database Theory, 2023

Causal What-If and How-To Analysis Using HypeR.

Fangzhu Shen, Kayvon Heravi, Oscar Gomez, Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

DPXPlain: Privately Explaining Aggregate Query Answers.

Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy

Proc. VLDB Endow., 2022

FEDEX: An Explainability Framework for Data Exploration Steps.

Daniel Deutch, Amir Gilad, Tova Milo, Amit Mualem, Amit Somech

Proc. VLDB Endow., 2022

Understanding Queries by Conditional Instances.

Amir Gilad, Zhengjie Miao, Sudeepa Roy, Jun Yang

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach.

Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

Detecting Treatment Effect Modifiers in Social Networks.

Amir Gilad, Harsh Parikh, Babak Salimi, Sudeepa Roy

CoRR, 2021

Synthesizing Linked Data Under Cardinality and Integrity Constraints.

Amir Gilad, Shweta Patwa, Ashwin Machanavajjhala

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

On Optimizing the Trade-off between Privacy and Utility in Data Provenance.

Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

PITA: Privacy Through Provenance Abstraction.

Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Explanations for Data Repair Through Shapley Values.

Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Data Provenance for Non-Experts

Amir Gilad

PhD thesis, 2020

Explaining Natural Language query results.

Daniel Deutch, Nave Frost, Amir Gilad

VLDB J., 2020

MuSe: Multiple Deletion Semantics for Data Repair.

Amir Gilad, Yihao Hu, Daniel Deutch, Sudeepa Roy

Proc. VLDB Endow., 2020

ExplainED: Explanations for EDA Notebooks.

Daniel Deutch, Amir Gilad, Tova Milo, Amit Somech

Proc. VLDB Endow., 2020

On Multiple Semantics for Declarative Database Repairs.

Amir Gilad, Daniel Deutch, Sudeepa Roy

Proceedings of the 2020 International Conference on Management of Data, 2020

T-REx: Table Repair Explanations.

Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer

Proceedings of the 2020 International Conference on Management of Data, 2020

Explaining Missing Query Results in Natural Language.

Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich

Proceedings of the 23rd International Conference on Extending Database Technology, 2020

Towards Inferring Queries from Simple and Partial Provenance Examples.

Amir Gilad, Yuval Moskovitch

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Reverse-Engineering Conjunctive Queries from Provenance Examples.

Daniel Deutch, Amir Gilad

Proceedings of the Advances in Database Technology, 2019

2018

Efficient provenance tracking for datalog using top-k queries.

Daniel Deutch, Amir Gilad, Yuval Moskovitch

VLDB J., 2018

Natural Language Explanations for Query Results.

Daniel Deutch, Nave Frost, Amir Gilad

SIGMOD Rec., 2018

NLProveNAns: Natural Language Provenance for Non-Answers.

Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich

Proc. VLDB Endow., 2018

QuestPro: Queries in SPARQL Through Provenance.

Efrat Abramovitz, Daniel Deutch, Amir Gilad

Proc. VLDB Endow., 2018

Provenance for Non-Experts.

Daniel Deutch, Nave Frost, Amir Gilad

IEEE Data Eng. Bull., 2018

Interactive Inference of SPARQL Queries Using Provenance.

Efrat Abramovitz, Daniel Deutch, Amir Gilad

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017

Provenance for Natural Language Queries.

Daniel Deutch, Nave Frost, Amir Gilad

Proc. VLDB Endow., 2017

2016

NLProv: Natural Language Provenance.

Daniel Deutch, Nave Frost, Amir Gilad

Proc. VLDB Endow., 2016

Learning Queries from Examples and Their Explanations.

Daniel Deutch, Amir Gilad

CoRR, 2016

QPlain: Query by explanation.

Daniel Deutch, Amir Gilad

Proceedings of the 32nd IEEE International Conference on Data Engineering, 2016

2015

Selective Provenance for Datalog Programs Using Top-K Queries.

Daniel Deutch, Amir Gilad, Yuval Moskovitch

Proc. VLDB Endow., 2015

Towards web-scale how-provenance.

Daniel Deutch, Amir Gilad, Yuval Moskovitch

Proceedings of the 31st IEEE International Conference on Data Engineering Workshops, 2015

selP: Selective tracking and presentation of data provenance.

Daniel Deutch, Amir Gilad, Yuval Moskovitch

Proceedings of the 31st IEEE International Conference on Data Engineering, 2015