19 citations · 26 across the 5 of their papers we have counts for
7 papers
Trustworthy AI
Richa Singh, Mayank Vatsa, Nalini Ratha
Modern AI systems are reaping the advantage of novel learning methods. With their increasing usage, we are realizing the limitations and shortfalls of these systems. Brittleness to…
Transforming Probabilistic Programs for Model Checking
Ryan Bernstein, Matthijs Vákár, Jeannette Wing
Probabilistic programming is perfectly suited to reliable and transparent data science, as it allows the user to specify their models in a high-level language without worrying abou…
Ensuring Fairness Beyond the Training Data
Debmalya Mandal, Samuel Deng, Suman Jana +2
We initiate the study of fair classifiers that are robust to perturbations in the training distribution. Despite recent progress, the literature on fairness has largely ignored the…
Ten Research Challenge Areas in Data Science
Jeannette M. Wing
Although data science builds on knowledge from computer science, mathematics, statistics, and other disciplines, data science is a unique field with many mysteries to unlock: chall…
Inverse Privacy
Yuri Gurevich, Efim Hudis, Jeannette M. Wing
An item of your personal information is inversely private if some party has access to it but you do not. We analyze the provenance of inversely private information and its rise to…
A Methodology for Information Flow Experiments
Michael Carl Tschantz, Amit Datta, Anupam Datta +1
Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited informat…