3 papers
cs.GT2025
Measuring the Hidden Cost of Data Valuation through Collective Disclosure
Patrick Mesana, Gilles Caporossi, Sebastien Gambs
Data valuation methods assign marginal utility to each data point that has contributed to the training of a machine learning model. If used directly as a payout mechanism, this cre…
cs.LG2025
WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles
Patrick Mesana, Clément Bénesse, Hadrien Lautraite +2
In this paper, we introduce WaKA (Wasserstein K-nearest-neighbors Attribution), a novel attribution method that leverages principles from the LiRA (Likelihood Ratio Attack) framewo…
cs.LG2025
On the Usage of Gaussian Process for Efficient Data Valuation
Clément Bénesse, Patrick Mesana, Athénaïs Gautier +1
In machine learning, knowing the impact of a given datum on model training is a fundamental task referred to as Data Valuation. Building on previous works from the literature, we h…