Huge amounts of unstructured data including image, video, audio, and text are ubiquitously
generated and shared, and it is a challenge to protect sensitive personal information in …

The introduction of online social networks (OSN) has transformed the way people connect
and interact with each other as well as share information. OSN have led to a tremendous …

We give efficient protocols and matching accuracy lower bounds for frequency estimation in
the local model for differential privacy. In this model, individual users randomize their data …

Interactive querying of a database degrades the privacy level. In this paper we answer the
fundamental question of characterizing the level of privacy degradation as a function of the …

Local differential privacy has recently surfaced as a strong measure of privacy in contexts
where personal information remains private even from data analysts. Working in a setting …

A large amount of valuable information resides in decentralized social graphs, where no
entity has access to the complete graph structure. Instead, each user maintains locally a …

Graph structured data have enabled several successful applications such as
recommendation systems and traffic prediction, given the rich node features and edges …

Cross Domain Recommendation (CDR) has been popularly studied to alleviate the cold-
start and data sparsity problem commonly existed in recommender systems. CDR models …

We give the first polynomial-time algorithm to estimate the mean of ad-variate probability
distribution with bounded covariance from Õ (d) independent samples subject to pure …

Differentially private SGD (DP-SGD) is one of the most popular methods for solving
differentially private empirical risk minimization (ERM). Due to its noisy perturbation on each …