no code implementations • 28 May 2024 • Saswat Das, Marco Romanelli, Cuong Tran, Zarreen Reza, Bhavya Kailkhura, Ferdinando Fioretto
Low-rank approximation techniques have become the de facto standard for fine-tuning Large Language Models (LLMs) due to their reduced computational and memory requirements.
no code implementations • 6 Feb 2024 • Saswat Das, Marco Romanelli, Ferdinando Fioretto
Ensuring privacy-preserving inference on cryptographically secure data is a well-known computational challenge.
no code implementations • 28 Jan 2023 • Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck, Saswat Das, Christine Task
The results show that, contrary to popular beliefs, traditional differential privacy techniques may be superior in terms of accuracy and fairness to differential private counterparts of widely used DA mechanisms.