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← Authors

Haim Kaplan

22 papers · 2018–2025 · 6 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+9 more ↓ 🌍 Conference Polyglot (6) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (7)
🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (6) 🏃 Academic Marathon (7) 🤝 Dynamic Duo (19) 🔬 Deep Specialist (12) 💎 Century Club (22) 🗃️ Keyword Collector (89) ⚡ Prolific Year (8) 🔥 Unstoppable (8)

Conferences

ICML (7) NIPS (7) COLT (4) ALT (2) AAAI (1) UAI (1)

Top co-authors

Yishay Mansour (19) Uri Stemmer (14) Alon Cohen (5) Shay Moran (4) Eliad Tsfadia (3) Tom Zahavy (3) Tomer Koren (2) Jay Tenenbaum (2) Edith Cohen (2) Avinatan Hasidim (2)

Research topics

Differential Privacy (5)

Keywords

differential privacy (11) regret bound (4) online algorithm (4) sample complexity (3) k-means clustering (2) reinforcement learning (2) privacy-preserving learning (2) shuffle model (2) online learning (2) private learning (2) markov decision process (2) apprenticeship learning (2) streaming algorithm (2) pac learning (1) assignment problem (1) policy evaluation (1) statistical learning theory (1) outlier detection (1) policy optimization (1) learning theory (1)

Papers

Nearly Optimal Sample Complexity for Learning with Label Proportions ICML 2025 Learning-Augmented Algorithms with Explicit Predictors NIPS 2024 Black-Box Differential Privacy for Interactive ML NIPS 2023 Concurrent Shuffle Differential Privacy Under Continual Observation ICML 2023 FriendlyCore: Practical Differentially Private Aggregation ICML 2022 Monotone Learning COLT 2022 Differentially Private Approximate Quantiles ICML 2022 Differentially-Private Clustering of Easy Instances ICML 2021 The Sparse Vector Technique, Revisited COLT 2021 Online Markov Decision Processes with Aggregate Bandit Feedback COLT 2021 Differentially Private Multi-Armed Bandits in the Shuffle Model NIPS 2021 Unknown mixing times in apprenticeship and reinforcement learning UAI 2020 Adversarially Robust Streaming Algorithms via Differential Privacy NIPS 2020 Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity NIPS 2020 Apprenticeship Learning via Frank-Wolfe AAAI 2020 Thompson Sampling for Adversarial Bit Prediction ALT 2020 Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies ALT 2020 Privately Learning Thresholds: Closing the Exponential Gap COLT 2020 Near-optimal Regret Bounds for Stochastic Shortest Path ICML 2020 Differentially Private Learning of Geometric Concepts ICML 2019 Learning to Screen NIPS 2019 Differentially Private k-Means with Constant Multiplicative Error NIPS 2018