Search Results for author: Babak Salimi

Found 10 papers, 0 papers with code

Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals

no code implementations22 Mar 2021 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 to scrutinize and trust them.

Decision Making Explainable artificial intelligence

Causal Relational Learning

no code implementations7 Apr 2020 Babak Salimi, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, Dan Suciu

Causal inference is at the heart of empirical research in natural and social sciences and is critical for scientific discovery and informed decision making.

Causal Inference Decision Making +1

Data Management for Causal Algorithmic Fairness

no code implementations20 Aug 2019 Babak Salimi, Bill Howe, Dan Suciu

Fairness is increasingly recognized as a critical component of machine learning systems.


Capuchin: Causal Database Repair for Algorithmic Fairness

no code implementations21 Feb 2019 Babak Salimi, Luke Rodriguez, Bill Howe, Dan Suciu

However, it is the underlying data on which these systems are trained that often reflect discrimination, suggesting a database repair problem.


A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence

no code implementations8 Aug 2017 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 variables, and is critical in making sound data driven decisions and policies in a multitude of applications.

Causal Inference

Causes for Query Answers from Databases: Datalog Abduction, View-Updates, and Integrity Constraints

no code implementations6 Nov 2016 Leopoldo Bertossi, Babak Salimi

In this work we establish precise connections between QA-causality and both abductive diagnosis and the view-update problem in databases, allowing us to obtain new algorithmic and complexity results for QA-causality.

ZaliQL: A SQL-Based Framework for Drawing Causal Inference from Big Data

no code implementations12 Sep 2016 Babak Salimi, Dan Suciu

In this paper we describe a suite of techniques for expressing causal inference tasks from observational data in SQL.

Causal Inference

Causes for Query Answers from Databases, Datalog Abduction and View-Updates: The Presence of Integrity Constraints

no code implementations20 Feb 2016 Babak Salimi, Leopoldo Bertossi

In this work we further investigate connections between query-answer causality and abductive diagnosis and the view-update problem.

From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back

no code implementations1 Jul 2015 Leopoldo Bertossi, Babak Salimi

In this work we establish and investigate connections between causes for query answers in databases, database repairs wrt.

Query-Answer Causality in Databases: Abductive Diagnosis and View-Updates

no code implementations13 Jun 2015 Babak Salimi, Leopoldo Bertossi

Causality has been recently introduced in databases, to model, characterize and possibly compute causes for query results (answers).

Cannot find the paper you are looking for? You can Submit a new open access paper.