Author

Viktor Schlegel

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#machine learning May 2026

Jacobian-Guided Anisotropic Noise Reshaping for Enhancing Representation Utility under Local Differential Privacy

This work proposes a novel approach that mitigates noise in task-relevant subspaces of the data representation by identifying task-critical subspaces via the Jacobian of a public downstream model, selectively attenuates noise along these directions, and reshapes the isotropic noise of standard LDP mechanisms into an an...

Young-Mok Ha, Viktor Schlegel, Yi-Dan Sun et al. · arXiv.org · 0 citations

#natural language process... Preprint Sep 2025

Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies

Compared to existing DP text generation baselines, Term2Note substantially improves both fidelity and utility, without relying on label distribution assumptions, highlighting its effectiveness as a practical privacy-preserving alternative to real clinical notes.

Yuping Wu, Viktor Schlegel, Warren Del-Pinto et al. · 2 citations