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
Term2Note: Synthesising Differentially Private Clinical Notes from Medical Terms
Yuping Wu, Viktor Schlegel, Warren Del-Pinto +10
Training data is fundamental to the success of modern machine learning models, yet in high-stakes domains such as healthcare, the use of real-world training data is severely constr…