108 citations · 129 across the 5 of their papers we have counts for
5 papers
A Framework for Auditable Synthetic Data Generation
Florimond Houssiau, Samuel N. Cohen, Lukasz Szpruch +5
Synthetic data has gained significant momentum thanks to sophisticated machine learning tools that enable the synthesis of high-dimensional datasets. However, many generation techn…
TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data
Florimond Houssiau, James Jordon, Samuel N. Cohen +6
Personal data collected at scale promises to improve decision-making and accelerate innovation. However, sharing and using such data raises serious privacy concerns. A promising so…
Synthetic Data -- what, why and how?
James Jordon, Lukasz Szpruch, Florimond Houssiau +5
This explainer document aims to provide an overview of the current state of the rapidly expanding work on synthetic data technologies, with a particular focus on privacy. The artic…
Identifiability in inverse reinforcement learning
Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch
Inverse reinforcement learning attempts to reconstruct the reward function in a Markov decision problem, using observations of agent actions. As already observed in Russell [1998]…
Black-box model risk in finance
Samuel N. Cohen, Derek Snow, Lukasz Szpruch
Machine learning models are increasingly used in a wide variety of financial settings. The difficulty of understanding the inner workings of these systems, combined with their wide…