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ORCIDYishay Mansour
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- affiliation: Tel Aviv University, School of Computer Science, Israel
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2020 – today
- 2023
[c280]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. ALT 2023: 471-509- [i135]Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer:
Concurrent Shuffle Differential Privacy Under Continual Observation. CoRR abs/2301.12535 (2023) - [i134]Uri Sherman, Tomer Koren, Yishay Mansour:
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation. CoRR abs/2301.13087 (2023) - [i133]Yogev Bar-On, Yishay Mansour:
Uniswap Liquidity Provision: An Online Learning Approach. CoRR abs/2302.00610 (2023) - [i132]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. CoRR abs/2302.01517 (2023) - [i131]Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter:
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. CoRR abs/2302.03805 (2023) - [i130]Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer:
On Differentially Private Online Predictions. CoRR abs/2302.14099 (2023) - [i129]Orin Levy, Alon Cohen, Asaf B. Cassel, Yishay Mansour:
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation. CoRR abs/2303.01464 (2023) - [i128]Dana Azouri, Oz Granit, Michael Alburquerque, Yishay Mansour, Tal Pupko, Itay Mayrose:
The tree reconstruction game: phylogenetic reconstruction using reinforcement learning. CoRR abs/2303.06695 (2023) - 2022
- [j110]Shant Boodaghians, Federico Fusco
, Stefano Leonardi, Yishay Mansour, Ruta Mehta:
Online revenue maximization for server pricing. Auton. Agents Multi Agent Syst. 36(1): 11 (2022) - [j109]Yishay Mansour, Alex Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu:
Bayesian Exploration: Incentivizing Exploration in Bayesian Games. Oper. Res. 70(2): 1105-1127 (2022) - [j108]Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer:
Adversarially Robust Streaming Algorithms via Differential Privacy. J. ACM 69(6): 42:1-42:14 (2022) - [j107]Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer:
Differentially Private Learning of Geometric Concepts. SIAM J. Comput. 51(4): 952-974 (2022) - [c279]Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour:
Modeling Attrition in Recommender Systems with Departing Bandits. AAAI 2022: 6072-6079 - [c278]Tal Lancewicki, Aviv Rosenberg, Yishay Mansour:
Learning Adversarial Markov Decision Processes with Delayed Feedback. AAAI 2022: 7281-7289 - [c277]Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer:
Monotone Learning. COLT 2022: 842-866 - [c276]Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Strategizing against Learners in Bayesian Games. COLT 2022: 5221-5252 - [c275]Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan:
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. ICML 2022: 4666-4689 - [c274]Tal Lancewicki, Aviv Rosenberg, Yishay Mansour:
Cooperative Online Learning in Stochastic and Adversarial MDPs. ICML 2022: 11918-11968 - [c273]Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer:
FriendlyCore: Practical Differentially Private Aggregation. ICML 2022: 21828-21863 - [c272]Idan Attias, Steve Hanneke, Yishay Mansour:
A Characterization of Semi-Supervised Adversarially Robust PAC Learnability. NeurIPS 2022 - [c271]Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg:
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. NeurIPS 2022 - [c270]Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman:
Benign Underfitting of Stochastic Gradient Descent. NeurIPS 2022 - [c269]Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. NeurIPS 2022 - [c268]Amos Beimel, Haim Kaplan, Yishay Mansour, Kobbi Nissim, Thatchaphol Saranurak, Uri Stemmer:
Dynamic algorithms against an adaptive adversary: generic constructions and lower bounds. STOC 2022: 1671-1684 - [i127]Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. CoRR abs/2201.12947 (2022) - [i126]Tal Lancewicki, Aviv Rosenberg, Yishay Mansour:
Cooperative Online Learning in Stochastic and Adversarial MDPs. CoRR abs/2201.13170 (2022) - [i125]Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg:
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. CoRR abs/2201.13172 (2022) - [i124]Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer:
Monotone Learning. CoRR abs/2202.05246 (2022) - [i123]Idan Attias, Steve Hanneke, Yishay Mansour:
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability. CoRR abs/2202.05420 (2022) - [i122]Eitan-Hai Mashiah, Idan Attias, Yishay Mansour:
Stochastic Strategic Patient Buyers: Revenue maximization using posted prices. CoRR abs/2202.06143 (2022) - [i121]Lee Cohen, Yishay Mansour, Michal Moshkovitz:
Finding Safe Zones of policies Markov Decision Processes. CoRR abs/2202.11593 (2022) - [i120]Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman:
Benign Underfitting of Stochastic Gradient Descent. CoRR abs/2202.13361 (2022) - [i119]Orin Levy, Yishay Mansour:
Learning Efficiently Function Approximation for Contextual MDP. CoRR abs/2203.00995 (2022) - [i118]Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour:
Modeling Attrition in Recommender Systems with Departing Bandits. CoRR abs/2203.13423 (2022) - [i117]Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Strategizing against Learners in Bayesian Games. CoRR abs/2205.08562 (2022) - [i116]Yishay Mansour, Richard Nock, Robert C. Williamson:
What killed the Convex Booster ? CoRR abs/2205.09628 (2022) - [i115]Yishay Mansour, Michal Moshkovitz, Cynthia Rudin:
There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes. CoRR abs/2206.04266 (2022) - [i114]Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan:
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. CoRR abs/2206.09421 (2022) - [i113]Orin Levy, Yishay Mansour:
Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP. CoRR abs/2207.11126 (2022) - [i112]Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, Yishay Mansour:
Regret Minimization and Convergence to Equilibria in General-sum Markov Games. CoRR abs/2207.14211 (2022) - [i111]Aadirupa Saha, Tomer Koren, Yishay Mansour:
Dueling Convex Optimization with General Preferences. CoRR abs/2210.02562 (2022) - [i110]Orin Levy, Asaf B. Cassel, Alon Cohen, Yishay Mansour:
Counterfactual Optimism: Rate Optimal Regret for Stochastic Contextual MDPs. CoRR abs/2211.14932 (2022) - [i109]Olivier Bousquet, Haim Kaplan, Aryeh Kontorovich, Yishay Mansour, Shay Moran, Menachem Sadigurschi, Uri Stemmer:
Differentially-Private Bayes Consistency. CoRR abs/2212.04216 (2022) - 2021
- [c267]Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu:
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. AISTATS 2021: 2332-2340 - [c266]Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour:
Online Markov Decision Processes with Aggregate Bandit Feedback. COLT 2021: 1301-1329 - [c265]Haim Kaplan, Yishay Mansour, Uri Stemmer:
The Sparse Vector Technique, Revisited. COLT 2021: 2747-2776 - [c264]Haim Kaplan, Yishay Mansour, Kobbi Nissim, Uri Stemmer:
Separating Adaptive Streaming from Oblivious Streaming Using the Bounded Storage Model. CRYPTO (3) 2021: 94-121 - [c263]Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia:
Differentially-Private Clustering of Easy Instances. ICML 2021: 2049-2059 - [c262]Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour:
Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions. ICML 2021: 5969-5978 - [c261]Aadirupa Saha, Tomer Koren, Yishay Mansour:
Adversarial Dueling Bandits. ICML 2021: 9235-9244 - [c260]Aadirupa Saha, Tomer Koren, Yishay Mansour:
Dueling Convex Optimization. ICML 2021: 9245-9254 - [c259]Aviv Rosenberg, Yishay Mansour:
Stochastic Shortest Path with Adversarially Changing Costs. IJCAI 2021: 2936-2942 - [c258]Uri Sherman, Tomer Koren, Yishay Mansour:
Optimal Rates for Random Order Online Optimization. NeurIPS 2021: 2097-2108 - [c257]Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet:
A New Theoretical Framework for Fast and Accurate Online Decision-Making. NeurIPS 2021: 9152-9166 - [c256]Aviv Rosenberg, Yishay Mansour:
Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure. NeurIPS 2021: 11148-11159 - [c255]Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan:
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. NeurIPS 2021: 19033-19045 - [c254]Lee Cohen, Ulrike Schmidt-Kraepelin, Yishay Mansour:
Dueling Bandits with Team Comparisons. NeurIPS 2021: 20633-20644 - [c253]Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer:
Differentially Private Multi-Armed Bandits in the Shuffle Model. NeurIPS 2021: 24956-24967 - [c252]Alon Cohen, Yonathan Efroni, Yishay Mansour, Aviv Rosenberg:
Minimax Regret for Stochastic Shortest Path. NeurIPS 2021: 28350-28361 - [i108]Haim Kaplan, Yishay Mansour, Kobbi Nissim, Uri Stemmer:
Separating Adaptive Streaming from Oblivious Streaming. CoRR abs/2101.10836 (2021) - [i107]Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour:
Online Markov Decision Processes with Aggregate Bandit Feedback. CoRR abs/2102.00490 (2021) - [i106]Nir Andelman, Michal Feldman, Amos Fiat, Yishay Mansour:
Competitive Equilibria with Unequal Budgets: Supporting Arbitrary Pareto Optimal Allocations. CoRR abs/2103.08634 (2021) - [i105]Alon Cohen, Yonathan Efroni, Yishay Mansour, Aviv Rosenberg:
Minimax Regret for Stochastic Shortest Path. CoRR abs/2103.13056 (2021) - [i104]Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour:
Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions. CoRR abs/2106.02436 (2021) - [i103]Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer:
Differentially Private Multi-Armed Bandits in the Shuffle Model. CoRR abs/2106.02900 (2021) - [i102]Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan:
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. CoRR abs/2106.11519 (2021) - [i101]Uri Sherman, Tomer Koren, Yishay Mansour:
Optimal Rates for Random Order Online Optimization. CoRR abs/2106.15207 (2021) - [i100]Lee Cohen, Ulrike Schmidt-Kraepelin, Yishay Mansour:
Dueling Bandits with Team Comparisons. CoRR abs/2107.02738 (2021) - [i99]Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer:
FriendlyCore: Practical Differentially Private Aggregation. CoRR abs/2110.10132 (2021) - [i98]Amos Beimel, Haim Kaplan, Yishay Mansour, Kobbi Nissim, Thatchaphol Saranurak, Uri Stemmer:
Dynamic Algorithms Against an Adaptive Adversary: Generic Constructions and Lower Bounds. CoRR abs/2111.03980 (2021) - [i97]Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour:
Nonstochastic Bandits with Composite Anonymous Feedback. CoRR abs/2112.02866 (2021) - [i96]Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia:
Differentially-Private Clustering of Easy Instances. CoRR abs/2112.14445 (2021) - 2020
- [j106]Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis:
Bayesian Incentive-Compatible Bandit Exploration. Oper. Res. 68(4): 1132-1161 (2020) - [c251]Michal Feldman, Yishay Mansour, Noam Nisan, Sigal Oren, Moshe Tennenholtz:
Designing Committees for Mitigating Biases. AAAI 2020: 1942-1949 - [c250]Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour:
Apprenticeship Learning via Frank-Wolfe. AAAI 2020: 6720-6728 - [c249]Yuval Lewi, Haim Kaplan, Yishay Mansour:
Thompson Sampling for Adversarial Bit Prediction. ALT 2020: 518-553 - [c248]Idan Rejwan, Yishay Mansour:
Top-$k$ Combinatorial Bandits with Full-Bandit Feedback. ALT 2020: 752-776 - [c247]Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour:
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies. ALT 2020: 906-934 - [c246]Haim Kaplan, Katrina Ligett, Yishay Mansour, Moni Naor, Uri Stemmer:
Privately Learning Thresholds: Closing the Exponential Gap. COLT 2020: 2263-2285 - [c245]Lee Cohen, Zachary C. Lipton, Yishay Mansour:
Efficient Candidate Screening Under Multiple Tests and Implications for Fairness. FORC 2020: 1:1-1:20 - [c244]Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan:
Near-optimal Regret Bounds for Stochastic Shortest Path. ICML 2020: 8210-8219 - [c243]Shant Boodaghians, Federico Fusco, Stefano Leonardi, Yishay Mansour, Ruta Mehta:
Online Revenue Maximization for Server Pricing. IJCAI 2020: 4106-4112 - [c242]Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni:
Prediction with Corrupted Expert Advice. NeurIPS 2020 - [c241]Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan:
Reinforcement Learning with Feedback Graphs. NeurIPS 2020 - [c240]Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer:
Adversarially Robust Streaming Algorithms via Differential Privacy. NeurIPS 2020 - [c239]Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia:
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity. NeurIPS 2020 - [c238]Eliran Shabat, Lee Cohen, Yishay Mansour:
Sample Complexity of Uniform Convergence for Multicalibration. NeurIPS 2020 - [c237]Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour:
Unknown mixing times in apprenticeship and reinforcement learning. UAI 2020: 430-439 - [i95]Alon Cohen, Haim Kaplan, Yishay Mansour, Aviv Rosenberg:
Near-optimal Regret Bounds for Stochastic Shortest Path. CoRR abs/2002.09869 (2020) - [i94]Idan Amir, Idan Attias, Tomer Koren, Roi Livni, Yishay Mansour:
Prediction with Corrupted Expert Advice. CoRR abs/2002.10286 (2020) - [i93]Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh:
Three Approaches for Personalization with Applications to Federated Learning. CoRR abs/2002.10619 (2020) - [i92]Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer:
Adversarially Robust Streaming Algorithms via Differential Privacy. CoRR abs/2004.05975 (2020) - [i91]Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia:
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity. CoRR abs/2004.07839 (2020) - [i90]Eliran Shabat, Lee Cohen, Yishay Mansour:
Sample Complexity of Uniform Convergence for Multicalibration. CoRR abs/2005.01757 (2020) - [i89]Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan:
Reinforcement Learning with Feedback Graphs. CoRR abs/2005.03789 (2020) - [i88]Aviv Rosenberg, Yishay Mansour:
Adversarial Stochastic Shortest Path. CoRR abs/2006.11561 (2020) - [i87]Yishay Mansour, Mehryar Mohri, Ananda Theertha Suresh, Ke Wu:
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. CoRR abs/2007.09762 (2020) - [i86]Guy Aridor, Yishay Mansour, Aleksandrs Slivkins, Zhiwei Steven Wu:
Competing Bandits: The Perils of Exploration Under Competition. CoRR abs/2007.10144 (2020) - [i85]Raphael Fettaya, Yishay Mansour:
Detecting malicious PDF using CNN. CoRR abs/2007.12729 (2020) - [i84]Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri:
Beyond Individual and Group Fairness. CoRR abs/2008.09490 (2020) - [i83]Aviv Rosenberg, Yishay Mansour:
Oracle-Efficient Reinforcement Learning in Factored MDPs with Unknown Structure. CoRR abs/2009.05986 (2020) - [i82]Haim Kaplan, Yishay Mansour, Uri Stemmer:
The Sparse Vector Technique, Revisited. CoRR abs/2010.00917 (2020) - [i81]Avrim Blum, Yishay Mansour:
Kidney exchange and endless paths: On the optimal use of an altruistic donor. CoRR abs/2010.01645 (2020) - [i80]Aadirupa Saha, Tomer Koren, Yishay Mansour:
Adversarial Dueling Bandits. CoRR abs/2010.14563 (2020) - [i79]Tal Lancewicki, Aviv Rosenberg, Yishay Mansour:
Learning Adversarial Markov Decision Processes with Delayed Feedback. CoRR abs/2012.14843 (2020)
2010 – 2019
- 2019
- [j105]Amos Fiat, Elias Koutsoupias, Katrina Ligett, Yishay Mansour, Svetlana Olonetsky:
Beyond myopic best response (in Cournot competition). Games Econ. Behav. 113: 38-57 (2019) - [j104]Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour:
Delay and Cooperation in Nonstochastic Bandits. J. Mach. Learn. Res. 20: 17:1-17:38 (2019) - [j103]Noga Alon, Michal Feldman, Yishay Mansour, Sigal Oren, Moshe Tennenholtz:
Dynamics of Evolving Social Groups. ACM Trans. Economics and Comput. 7(3): 14:1-14:27 (2019) - [c236]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved Generalization Bounds for Robust Learning. ALT 2019: 162-183 - [c235]Amit Daniely, Yishay Mansour:
Competitive ratio vs regret minimization: achieving the best of both worlds. ALT 2019: 333-368 - [c234]Lee Cohen, Yishay Mansour:
Optimal Algorithm for Bayesian Incentive-Compatible Exploration. EC 2019: 135-151 - [c233]Alon Cohen, Tomer Koren, Yishay Mansour:
Learning Linear-Quadratic Regulators Efficiently with only √T Regret. ICML 2019: 1300-1309 - [c232]Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer:
Differentially Private Learning of Geometric Concepts. ICML 2019: 3233-3241 - [c231]Alon Resler, Yishay Mansour:
Adversarial Online Learning with noise. ICML 2019: 5429-5437 - [c230]Aviv Rosenberg, Yishay Mansour:
Online Convex Optimization in Adversarial Markov Decision Processes. ICML 2019: 5478-5486 - [c229]Aviv Rosenberg, Yishay Mansour:
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function. NeurIPS 2019: 2209-2218 - [c228]Yogev Bar-On, Yishay Mansour:
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits. NeurIPS 2019: 3110-3120 - [c227]Roi Livni, Yishay Mansour:
Graph-based Discriminators: Sample Complexity and Expressiveness. NeurIPS 2019: 6696-6705 - [c226]Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran:
Learning to Screen. NeurIPS 2019: 8612-8621 - [i78]Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran:
Learning and Generalization for Matching Problems. CoRR abs/1902.04741 (2019) - [i77]Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer:
Differentially Private Learning of Geometric Concepts. CoRR abs/1902.05017 (2019) - [i76]Alon Cohen, Tomer Koren, Yishay Mansour:
Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret. CoRR abs/1902.06223 (2019) - [i75]Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour:
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies. CoRR abs/1902.10140 (2019) - [i74]