17 citations · 88 across the 19 of their papers we have counts for
20 papers
Causal Data Integration
Brit Youngmann, Michael Cafarella, Babak Salimi +1
Causal inference is fundamental to empirical scientific discoveries in natural and social sciences; however, in the process of conducting causal inference, data management problems…
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…
Heterogeneous Treatment Effects in Social Networks
Amir Gilad, Harsh Parikh, Sudeepa Roy +1
We study treatment effect modifiers for causal analysis in a social network, where neighbors' characteristics or network structure may affect the outcome of a unit, and the goal is…
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra, Romila Pradhan, Babak Salimi
There has been a recent resurgence of interest in explainable artificial intelligence (XAI) that aims to reduce the opaqueness of AI-based decision-making systems, allowing humans…
Causal Relational Learning
Babak Salimi, Harsh Parikh, Moe Kayali +3
Causal inference is at the heart of empirical research in natural and social sciences and is critical for scientific discovery and informed decision making. The gold standard in ca…
Mining Approximate Acyclic Schemes from Relations
Batya Kenig, Pranay Mundra, Guna Prasad +2
Acyclic schemes have numerous applications in databases and in machine learning, such as improved design, more efficient storage, and increased performance for queries and machine…
Data Management for Causal Algorithmic Fairness
Babak Salimi, Bill Howe, Dan Suciu
Fairness is increasingly recognized as a critical component of machine learning systems. However, it is the underlying data on which these systems are trained that often reflects d…
Capuchin: Causal Database Repair for Algorithmic Fairness
Babak Salimi, Luke Rodriguez, Bill Howe +1
Fairness is increasingly recognized as a critical component of machine learning systems. However, it is the underlying data on which these systems are trained that often reflect di…
MobilityMirror: Bias-Adjusted Transportation Datasets
Luke Rodriguez, Babak Salimi, Haoyue Ping +2
We describe customized synthetic datasets for publishing mobility data. Private companies are providing new transportation modalities, and their data is of high value for integrati…
Bias in OLAP Queries: Detection, Explanation, and Removal
Babak Salimi, Johannes Gehrke, Dan Suciu
On line analytical processing (OLAP) is an essential element of decision-support systems. OLAP tools provide insights and understanding needed for improved decision making. However…
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence
Sudeepa Roy, Babak Salimi
The study of causality or causal inference - how much a given treatment causally affects a given outcome in a population - goes way beyond correlation or association analysis of va…
Causes for Query Answers from Databases: Datalog Abduction, View-Updates, and Integrity Constraints
Leopoldo Bertossi, Babak Salimi
Causality has been recently introduced in databases, to model, characterize, and possibly compute causes for query answers. Connections between QA-causality and consistency-based d…
ZaliQL: A SQL-Based Framework for Drawing Causal Inference from Big Data
Babak Salimi, Dan Suciu
Causal inference from observational data is a subject of active research and development in statistics and computer science. Many toolkits have been developed for this purpose that…
Quantifying Causal Effects on Query Answering in Databases
Babak Salimi, Leopoldo Bertossi, Dan Suciu +1
The notion of actual causation, as formalized by Halpern and Pearl, has been recently applied to relational databases, to characterize and compute actual causes for possibly unexpe…
Causes for Query Answers from Databases, Datalog Abduction and View-Updates: The Presence of Integrity Constraints
Babak Salimi, Leopoldo Bertossi
Causality has been recently introduced in databases, to model, characterize and possibly compute causes for query results (answers). Connections between queryanswer causality, cons…
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back
Leopoldo Bertossi, Babak Salimi
In this work we establish and investigate connections between causes for query answers in databases, database repairs wrt. denial constraints, and consistency-based diagnosis. The…
Query-Answer Causality in Databases: Abductive Diagnosis and View-Updates
Babak Salimi, Leopoldo Bertossi
Causality has been recently introduced in databases, to model, characterize and possibly compute causes for query results (answers). Connections between query causality and consist…
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back
Babak Salimi, Leopoldo Bertossi
In this work we establish and investigate connections between causality for query answers in databases, database repairs wrt. denial constraints, and consistency-based diagnosis. T…
Unifying Causality, Diagnosis, Repairs and View-Updates in Databases
Leopoldo Bertossi, Babak Salimi
In this work we establish and point out connections between the notion of query-answer causality in databases and database repairs, model-based diagnosis in its consistency-based a…
Causality in Databases: The Diagnosis and Repair Connections
Babak Salimi, Leopoldo Bertossi
In this work we establish and investigate the connections between causality for query answers in databases, database repairs wrt. denial constraints, and consistency-based diagnosi…