108 citations · 126 across the 9 of their papers we have counts for
9 papers
Sola-Visibility-ISPM: Benchmarking Agentic AI for Identity Security Posture Management Visibility
Gal Engelberg, Konstantin Koutsyi, Leon Goldberg +5
Identity Security Posture Management (ISPM) is a core challenge for modern enterprises operating across cloud and SaaS environments. Answering basic ISPM visibility questions, such…
Understanding Transfer Learning via Mean-field Analysis
Gholamali Aminian, Łukasz Szpruch, Samuel N. Cohen
We propose a novel framework for exploring generalization errors of transfer learning through the lens of differential calculus on the space of probability measures. In particular,…
Generalization and Robustness of the Tilted Empirical Risk
Gholamali Aminian, Amir R. Asadi, Tian Li +3
The generalization error (risk) of a supervised statistical learning algorithm quantifies its prediction ability on previously unseen data. Inspired by exponential tilting, \citet{…
Generalization Error of Graph Neural Networks in the Mean-field Regime
Gholamali Aminian, Yixuan He, Gesine Reinert +2
This work provides a theoretical framework for assessing the generalization error of graph neural networks in the over-parameterized regime, where the number of parameters surpasse…
Mean-field Analysis of Generalization Errors
Gholamali Aminian, Samuel N. Cohen, Łukasz Szpruch
We propose a novel framework for exploring weak and generalization errors of algorithms through the lens of differential calculus on the space of probability measures. Specif…
Inefficiency of CFMs: hedging perspective and agent-based simulations
Samuel Cohen, Marc Sabaté Vidales, David Šiška +1
We investigate whether the fee income from trades on the CFM is sufficient for the liquidity providers to hedge away the exposure to market risk. We first analyse this problem thro…
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…