A Comprehensive Guide to Differential Privacy: From Theory to User Expectations
Authors: Napsu Karmitsa, Antti Airola, Tapio Pahikkala, Tinja Pitkämäki | Published: 2025-09-03
Differential Privacy
The Double-edged Sword of LLM-based Data Reconstruction: Understanding and Mitigating Contextual Vulnerability in Word-level Differential Privacy Text Sanitization
Authors: Stephen Meisenbacher, Alexandra Klymenko, Andreea-Elena Bodea, Florian Matthes | Published: 2025-08-26
SoK: Data Minimization in Machine Learning
Authors: Robin Staab, Nikola Jovanović, Kimberly Mai, Prakhar Ganesh, Martin Vechev, Ferdinando Fioretto, Matthew Jagielski | Published: 2025-08-14
Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning
Authors: Stephan Rabanser | Published: 2025-08-11
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
Authors: Bogdan Kulynych, Juan Felipe Gomez, Georgios Kaissis, Jamie Hayes, Borja Balle, Flavio du Pin Calmon, Jean Louis Raisaro | Published: 2025-07-09
Efficient Unlearning with Privacy Guarantees
Authors: Josep Domingo-Ferrer, Najeeb Jebreel, David Sánchez | Published: 2025-07-07
Tuning without Peeking: Provable Privacy and Generalization Bounds for LLM Post-Training
Authors: Ismail Labiad, Mathurin Videau, Matthieu Kowalski, Marc Schoenauer, Alessandro Leite, Julia Kempe, Olivier Teytaud | Published: 2025-07-02
Machine Learning with Privacy for Protected Attributes
Authors: Saeed Mahloujifar, Chuan Guo, G. Edward Suh, Kamalika Chaudhuri | Published: 2025-06-24
Learning Obfuscations Of LLM Embedding Sequences: Stained Glass Transform
Authors: Jay Roberts, Kyle Mylonakis, Sidhartha Roy, Kaan Kale | Published: 2025-06-11
Differentially Private Distribution Release of Gaussian Mixture Models via KL-Divergence Minimization
Authors: Hang Liu, Anna Scaglione, Sean Peisert | Published: 2025-06-04