12 citations · 18 across the 8 of their papers we have counts for
9 papers
Differentially Private Modeling of Disease Transmission within Human Contact Networks
Shlomi Hod, Debanuj Nayak, Jason R. Gantenberg +3
Epidemiologic studies of infectious diseases often rely on models of contact networks to capture the complex interactions that govern disease spread, and ongoing projects aim to va…
Observational Auditing of Label Privacy
Iden Kalemaj, Luca Melis, Maxime Boucher +2
Differential privacy (DP) auditing is essential for evaluating privacy guarantees in machine learning systems. Existing auditing methods, however, pose a significant challenge for…
PrivacyGuard: A Modular Framework for Privacy Auditing in Machine Learning
Luca Melis, Matthew Grange, Iden Kalemaj +4
The increasing deployment of Machine Learning (ML) models in sensitive domains motivates the need for robust, practical privacy assessment tools. PrivacyGuard is a comprehensive to…
Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation
Palak Jain, Iden Kalemaj, Sofya Raskhodnikova +2
Privacy is a central challenge for systems that learn from sensitive data sets, especially when a system's outputs must be continuously updated to reflect changing data. We conside…
Differentially Private Conditional Independence Testing
Iden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
Conditional independence (CI) tests are widely used in statistical data analysis, e.g., they are the building block of many algorithms for causal graph discovery. The goal of a CI…
Node-Differentially Private Estimation of the Number of Connected Components
Iden Kalemaj, Sofya Raskhodnikova, Adam Smith +1
We design the first node-differentially private algorithm for approximating the number of connected components in a graph. Given a database representing an -vertex graph and…
Sublinear-Time Computation in the Presence of Online Erasures
Iden Kalemaj, Sofya Raskhodnikova, Nithin Varma
We initiate the study of sublinear-time algorithms that access their input via an online adversarial erasure oracle. After answering each input query, such an oracle can erase …
Isoperimetric Inequalities for Real-Valued Functions with Applications to Monotonicity Testing
Hadley Black, Iden Kalemaj, Sofya Raskhodnikova
We generalize the celebrated isoperimetric inequality of Khot, Minzer, and Safra~(SICOMP 2018) for Boolean functions to the case of real-valued functions $f \colon \{0,1\}^d\to\mat…
Performative Prediction in a Stateful World
Gavin Brown, Shlomi Hod, Iden Kalemaj
Deployed supervised machine learning models make predictions that interact with and influence the world. This phenomenon is called performative prediction by Perdomo et al. (ICML 2…