Kaplan, Haim

24 publications

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 2024 Learning-Augmented Algorithms with Explicit Predictors Marek Eliáš, Haim Kaplan, Yishay Mansour, Shay Moran

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

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

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

COLT 2021 Online Markov Decision Processes with Aggregate Bandit Feedback Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour

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

AAAI 2020 Apprenticeship Learning via Frank-Wolfe Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

ICML 2020 Near-Optimal Regret Bounds for Stochastic Shortest Path Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan

ALT 2020 Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies Tom Zahavy, Avinatan Hasidim, Haim Kaplan, Yishay Mansour

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

ALT 2020 Thompson Sampling for Adversarial Bit Prediction Yuval Lewi, Haim Kaplan, Yishay Mansour

UAI 2020 Unknown Mixing Times in Apprenticeship and Reinforcement Learning Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

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

NeurIPS 2019 Learning to Screen Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran

AAAI 2018 Clustering Small Samples with Quality Guarantees: Adaptivity with One2all PPS Edith Cohen, Shiri Chechik, Haim Kaplan

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