8 citations · 8 across the 7 of their papers we have counts for
4 papers · 1 filter
Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes
Joonhyuk Ko, Juba Ziani, Saswat Das +2
Statistical agencies rely on sampling techniques to collect socio-demographic data crucial for policy-making and resource allocation. This paper shows that surveys of important soc…
Low-rank finetuning for LLMs: A fairness perspective
Saswat Das, Marco Romanelli, Cuong Tran +3
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. This pa…
Advances in Differential Privacy and Differentially Private Machine Learning
Saswat Das, Subhankar Mishra
There has been an explosion of research on differential privacy (DP) and its various applications in recent years, ranging from novel variants and accounting techniques in differen…
Disparate Impact on Group Accuracy of Linearization for Private Inference
Saswat Das, Marco Romanelli, Ferdinando Fioretto
Ensuring privacy-preserving inference on cryptographically secure data is a well-known computational challenge. To alleviate the bottleneck of costly cryptographic computations in…