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quant-ph2026
Private training in quantum machine learning
Tigran Sedrakyan, Frédéric Grosshans, Elham Kashefi
With the emergence of machine learning (ML) models trained on large datasets containing potentially sensitive data, a major question in AI safety is how to make learning private wi…
quant-ph2026
A unified framework for Bell inequalities from continuous-variable contextuality
Carlos Ernesto Lopetegui-González, Gaël Massé, Enky Oudot +6
Although the original EPR paradox was formulated in terms of position and momentum, most studies of these phenomena have focused on measurement scenarios with only a discrete numbe…