Stemmer, Uri

37 publications

ICML 2025 Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries Edith Cohen, Mihir Singhal, Uri Stemmer

ICML 2025 Nearly Optimal Sample Complexity for Learning with Label Proportions Robert Istvan Busa-Fekete, Travis Dick, Claudio Gentile, Haim Kaplan, Tomer Koren, Uri Stemmer

NeurIPS 2025 Private Set Union with Multiple Contributions Travis Dick, Haim Kaplan, Alex Kulesza, Uri Stemmer, Ziteng Sun, Ananda Theertha Suresh

NeurIPS 2025 The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for $\ell_2$ Norm Estimation Sara Ahmadian, Edith Cohen, Uri Stemmer

NeurIPS 2025 Tight Bounds for Answering Adaptively Chosen Concentrated Queries Emma Rapoport, Edith Cohen, Uri Stemmer

COLT 2024 Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer

ICML 2024 Private Truly-Everlasting Robust-Prediction Uri Stemmer

NeurIPS 2023 Adaptive Data Analysis in a Balanced Adversarial Model Kobbi Nissim, Uri Stemmer, Eliad Tsfadia

NeurIPS 2023 Black-Box Differential Privacy for Interactive ML Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer

ICML 2023 Concurrent Shuffle Differential Privacy Under Continual Observation Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer

NeurIPS 2023 Private Everlasting Prediction Moni Naor, Kobbi Nissim, Uri Stemmer, Chao Yan

AAAI 2023 Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer

ICML 2022 Adaptive Data Analysis with Correlated Observations Aryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer

ICML 2022 Differentially Private Approximate Quantiles Haim Kaplan, Shachar Schnapp, Uri Stemmer

ICML 2022 FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer

COLT 2022 Monotone Learning Olivier J Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer

ICML 2022 On the Robustness of CountSketch to Adaptive Inputs Edith Cohen, Xin Lyu, Jelani Nelson, Tamas Sarlos, Moshe Shechner, Uri Stemmer

AISTATS 2021 Differentially Private Weighted Sampling Edith Cohen, Ofir Geri, Tamas Sarlos, Uri Stemmer

NeurIPS 2021 Differentially Private Multi-Armed Bandits in the Shuffle Model Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer

ICML 2021 Differentially-Private Clustering of Easy Instances Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia

JMLR 2021 Locally Private K-Means Clustering Uri Stemmer

NeurIPS 2021 On the Sample Complexity of Privately Learning Axis-Aligned Rectangles Menachem Sadigurschi, Uri Stemmer

COLT 2021 The Sparse Vector Technique, Revisited Haim Kaplan, Yishay Mansour, Uri Stemmer

NeurIPS 2020 Adversarially Robust Streaming Algorithms via Differential Privacy Avinatan Hasidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer

COLT 2020 Closure Properties for Private Classification and Online Prediction Noga Alon, Amos Beimel, Shay Moran, Uri Stemmer

JMLR 2020 Practical Locally Private Heavy Hitters Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Thakurta

AISTATS 2020 Private K-Means Clustering with Stability Assumptions Moshe Shechner, Or Sheffet, Uri Stemmer

NeurIPS 2020 Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia

COLT 2020 Privately Learning Thresholds: Closing the Exponential Gap Haim Kaplan, Katrina Ligett, Yishay Mansour, Moni Naor, Uri Stemmer

JMLR 2019 Characterizing the Sample Complexity of Pure Private Learners Amos Beimel, Kobbi Nissim, Uri Stemmer

ICML 2019 Differentially Private Learning of Geometric Concepts Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer

COLT 2019 Private Center Points and Learning of Halfspaces Amos Beimel, Shay Moran, Kobbi Nissim, Uri Stemmer

JMLR 2019 Simultaneous Private Learning of Multiple Concepts Mark Bun, Kobbi Nissim, Uri Stemmer

ALT 2018 Clustering Algorithms for the Centralized and Local Models Kobbi Nissim, Uri Stemmer

NeurIPS 2018 Differentially Private K-Means with Constant Multiplicative Error Uri Stemmer, Haim Kaplan

NeurIPS 2018 The Limits of Post-Selection Generalization Jonathan Ullman, Adam Smith, Kobbi Nissim, Uri Stemmer, Thomas Steinke

NeurIPS 2017 Practical Locally Private Heavy Hitters Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Guha Thakurta