Uri Stemmer
36 papers · 2017–2025 · 9 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (9) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (8)
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Keyword Pioneer
🐝
Cross-Pollinator
(8)
🌉
Interdisciplinary Bridge
🏆
Keyword Champion
(27)
🤝
Dynamic Duo
(14)
🔬
Deep Specialist
(27)
🌱
Topic Pioneer
🗃️
Keyword Collector
(114)
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Prolific Year
(5)
💎
Century Club
(36)
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Unstoppable
(9)
📈
Trend Setter
Conferences
ICML (10)
NIPS (10)
COLT (6)
JMLR (4)
AISTATS (2)
AAAI (1)
ALT (1)
EMNLP (1)
NAACL (1)
Top co-authors
Research topics
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