← Authors

Uri Stemmer

36 papers · 2017–2025 · 9 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (43) 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (8) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (8) πŸŒ‰ Interdisciplinary Bridge πŸ† Keyword Champion (27) 🀝 Dynamic Duo (14) πŸ”¬ Deep Specialist (27) 🌱 Topic Pioneer πŸ—ƒοΈ Keyword Collector (114) ⚑ Prolific Year (5) πŸ’Ž Century Club (36) πŸ”₯ Unstoppable (9) πŸ“ˆ Trend Setter

Conferences

ICML (10) NIPS (10) COLT (6) JMLR (4) AISTATS (2) AAAI (1) ALT (1) EMNLP (1) NAACL (1)

Top co-authors

Haim Kaplan (14) Yishay Mansour (11) Kobbi Nissim (10) Edith Cohen (7) Shay Moran (4) Eliad Tsfadia (4) Tamas Sarlos (4) Yossi Matias (4) Amos Beimel (3) Jelani Nelson (3)

Research topics

Differential Privacy (9) Privacy (1)

Keywords

differential privacy (27) sample complexity (8) heavy hitter (5) k-means clustering (5) private learning (5) pac learning (4) pre-trained language model (2) clinical note (2) streaming algorithm (2) randomized algorithm (2) regret bound (2) statistical query (2) learning theory (2) privacy-preserving learning (2) dimensionality reduction (2) local privacy (2) generalization bound (2) vc dimension (2) online algorithm (2) privacy guarantee (2)

Papers

Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries ICML 2025
Nearly Optimal Sample Complexity for Learning with Label Proportions ICML 2025
Private Truly-Everlasting Robust-Prediction ICML 2024
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries COLT 2024
Black-Box Differential Privacy for Interactive ML NIPS 2023
Private Everlasting Prediction NIPS 2023
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs AAAI 2023
Concurrent Shuffle Differential Privacy Under Continual Observation ICML 2023
Adaptive Data Analysis in a Balanced Adversarial Model NIPS 2023
Adaptive Data Analysis with Correlated Observations ICML 2022
On the Robustness of CountSketch to Adaptive Inputs ICML 2022
Monotone Learning COLT 2022
FriendlyCore: Practical Differentially Private Aggregation ICML 2022
Differentially Private Approximate Quantiles ICML 2022
Learning and Evaluating a Differentially Private Pre-trained Language Model NAACL 2021
Differentially Private Multi-Armed Bandits in the Shuffle Model NIPS 2021
On the Sample Complexity of Privately Learning Axis-Aligned Rectangles NIPS 2021
Differentially Private Weighted Sampling AISTATS 2021
The Sparse Vector Technique, Revisited COLT 2021
Learning and Evaluating a Differentially Private Pre-trained Language Model EMNLP 2021
Differentially-Private Clustering of Easy Instances ICML 2021
Locally Private k-Means Clustering JMLR 2021
Adversarially Robust Streaming Algorithms via Differential Privacy NIPS 2020
Privately Learning Thresholds: Closing the Exponential Gap COLT 2020
Practical Locally Private Heavy Hitters JMLR 2020
Closure Properties for Private Classification and Online Prediction COLT 2020
Private k-Means Clustering with Stability Assumptions AISTATS 2020
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity NIPS 2020
Simultaneous Private Learning of Multiple Concepts JMLR 2019
Differentially Private Learning of Geometric Concepts ICML 2019
Private Center Points and Learning of Halfspaces COLT 2019
Characterizing the Sample Complexity of Pure Private Learners JMLR 2019
The Limits of Post-Selection Generalization NIPS 2018
Clustering Algorithms for the Centralized and Local Models ALT 2018
Differentially Private k-Means with Constant Multiplicative Error NIPS 2018
Practical Locally Private Heavy Hitters NIPS 2017