research
∙
05/15/2023
Causal Data Integration
Causal inference is fundamental to empirical scientific discoveries in n...
share
research
∙
12/21/2022
Consistent Range Approximation for Fair Predictive Modeling
This paper proposes a novel framework for certifying the fairness of pre...
research
∙
10/06/2022
On Explaining Confounding Bias
When analyzing large datasets, analysts are often interested in the expl...
research
∙
03/28/2022
HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach
What-if (provisioning for an update to a database) and how-to (how to mo...
research
∙
12/17/2021
Interpretable Data-Based Explanations for Fairness Debugging
A wide variety of fairness metrics and eXplainable Artificial Intelligen...
research
∙
03/22/2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
There has been a recent resurgence of interest in explainable artificial...
research
∙
04/07/2020
Causal Relational Learning
Causal inference is at the heart of empirical research in natural and so...
research
∙
11/29/2019
Mining Approximate Acyclic Schemes from Relations
Acyclic schemes have numerous applications in databases and in machine l...
research
∙
08/20/2019
Data Management for Causal Algorithmic Fairness
Fairness is increasingly recognized as a critical component of machine l...
research
∙
02/21/2019
Capuchin: Causal Database Repair for Algorithmic Fairness
Fairness is increasingly recognized as a critical component of machine l...
research
∙
08/21/2018
MobilityMirror: Bias-Adjusted Transportation Datasets
We describe customized synthetic datasets for publishing mobility data. ...
research
∙
03/12/2018
Bias in OLAP Queries: Detection, Explanation, and Removal
On line analytical processing (OLAP) is an essential element of decision...
research
∙
03/12/2018
HypDB: Detect, Explain And Resolve Bias in OLAP
On line analytical processing (OLAP) is an essential element of decision...
research
∙
08/08/2017
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence
The study of causality or causal inference - how much a given treatment ...
research
∙
11/06/2016
Causes for Query Answers from Databases: Datalog Abduction, View-Updates, and Integrity Constraints
Causality has been recently introduced in databases, to model, character...
research
∙
09/12/2016
ZaliQL: A SQL-Based Framework for Drawing Causal Inference from Big Data
Causal inference from observational data is a subject of active research...
research
∙
02/20/2016
Causes for Query Answers from Databases, Datalog Abduction and View-Updates: The Presence of Integrity Constraints
Causality has been recently introduced in databases, to model, character...
research
∙
06/13/2015
