Rachel Cummings

20 papers · 2015–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (36) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🏃 Academic Marathon (10) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (5) 🔬 Deep Specialist (13) 🗃️ Keyword Collector (82) 💎 Century Club (20) 🔥 Unstoppable (8) 📈 Trend Setter

Conferences

AISTATS (7) NIPS (5) ICML (4) COLT (2) AAAI (1) JMLR (1)

Top co-authors

Wanrong Zhang (5) Sara Krehbiel (4) Yajun Mei (3) Tingting Ou (2) Katrina Ligett (2) Rui Tuo (2) Saeyoung Rho (2) Yuliia Lut (2) Marco Avella Medina (2) Vishal Misra (2)

Research topics

Differential Privacy (5)

Keywords

differential privacy (14) change-point detection (3) regret bound (3) mechanism design (2) online learning (2) incentive compatibility (2) offline detection (2) online detection (2) false discovery rate (1) minimax optimality (1) active learning (1) pac learning (1) mean estimation (1) statistical learning (1) sample complexity (1) optimal transport (1) causal inference (1) stochastic process (1) linear regression (1) sequential hypothesis testing (1)

Papers

ClusterSC: Advancing Synthetic Control with Donor Selection AISTATS 2025

Differential Privacy Under Class Imbalance: Methods and Empirical Insights ICML 2025

Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model ICML 2025

Thompson Sampling Itself is Differentially Private AISTATS 2024

Differentially Private Synthetic Control AISTATS 2023

An active learning framework for multi-group mean estimation NIPS 2023

Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis AISTATS 2022

Mean Estimation with User-level Privacy under Data Heterogeneity NIPS 2022

Optimal Local Explainer Aggregation for Interpretable Prediction AAAI 2022

Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size AISTATS 2022

Single and Multiple Change-Point Detection with Differential Privacy JMLR 2021

Differentially Private Online Submodular Maximization AISTATS 2021

PAPRIKA: Private Online False Discovery Rate Control ICML 2021

Privately detecting changes in unknown distributions ICML 2020

Learning Auctions with Robust Incentive Guarantees NIPS 2019

Differentially Private Online Submodular Minimization AISTATS 2019

Differential Privacy for Growing Databases NIPS 2018

Differentially Private Change-Point Detection NIPS 2018

Adaptive Learning with Robust Generalization Guarantees COLT 2016

Truthful Linear Regression COLT 2015