Synthetic data generation methods, and in particular, private synthetic ...
Experimental and observational studies often lack validity due to untest...
Differential privacy (DP) is the state-of-the-art and rigorous notion of...
What-if (provisioning for an update to a database) and how-to (how to mo...
A powerful way to understand a complex query is by observing how it oper...
In many data analysis applications, there is a need to explain why a
sur...
dame-flame is a Python package for performing matching for observational...
We investigate the computational complexity of minimizing the source
sid...
We study the problem of database repairs through a rule-based framework ...
Local sensitivity of a query Q given a database instance D, i.e. how muc...
Causal inference is at the heart of empirical research in natural and so...
We propose a matching method for observational data that matches units w...
We propose a matching method that recovers direct treatment effects from...
We investigate the computational complexity of minimizing the source
sid...
Uncertainty in the estimation of the causal effect in observational stud...
In this paper we present a suite of methods to efficiently estimate coun...
How should a cleaning system measure the amount of inconsistency in the
...
For testing the correctness of SQL queries, e.g., evaluating student
sub...
We present a system for summarization and interactive exploration of
hig...
We aim to create the highest possible quality of treatment-control match...
We investigate the complexity of computing an optimal repair of an
incon...
Analyzing contention for resources in a cluster computing environment
ac...
The study of causality or causal inference - how much a given treatment
...
A classical problem in causal inference is that of matching, where treat...
The best current methods for exactly computing the number of satisfying
...