11 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Personalized Differential Privacy for Ridge Regression
Krishna Acharya, Franziska Boenisch, Rakshit Naidu +1
The increased application of machine learning (ML) in sensitive domains requires protecting the training data through privacy frameworks, such as differential privacy (DP). DP requ…
cs.CL2023★ 11 cited
Are Chatbots Ready for Privacy-Sensitive Applications? An Investigation into Input Regurgitation and Prompt-Induced Sanitization
Aman Priyanshu, Supriti Vijay, Ayush Kumar +2
LLM-powered chatbots are becoming widely adopted in applications such as healthcare, personal assistants, industry hiring decisions, etc. In many of these cases, chatbots are fed s…
cs.CR2022★ 1 cited
Can Causal (and Counterfactual) Reasoning improve Privacy Threat Modelling?
Rakshit Naidu, Navid Kagalwalla
Causal questions often permeate in our day-to-day activities. With causal reasoning and counterfactual intuition, privacy threats can not only be alleviated but also prevented. In…