2 papers
cs.LG2026
Jacobian-Guided Anisotropic Noise Reshaping for Enhancing Representation Utility under Local Differential Privacy
Youngmok Ha, Viktor Schlegel, Yidan Sun +1
While Local Differential Privacy (LDP) serves as a foundational primitive for distributed data collection, its stringent randomization requirements often lead to severe degradation…
cs.CL2025
Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies
Yuping Wu, Viktor Schlegel, Warren Del-Pinto +11
In high-stakes domains such as healthcare, privacy concerns severely limit the use of real-world training data. Differentially private (DP) synthetic data offers a promising altern…