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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
- 2025
[c306]Edith Cohen, Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer, Eliad Tsfadia:
Data Reconstruction: When You See It and When You Don't. ITCS 2025: 39:1-39:23- 2024
- [j114]Noa Ecker, Dorothée Huchon, Yishay Mansour, Itay Mayrose, Tal Pupko:
A machine-learning-based alternative to phylogenetic bootstrap. Bioinform. 40(Supplement_1): i208-i217 (2024) - [c305]Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler:
Principal-Agent Reward Shaping in MDPs. AAAI 2024: 9502-9510 - [c304]Aadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren:
Faster Convergence with MultiWay Preferences. AISTATS 2024: 433-441 - [c303]Nave Frost, Zachary C. Lipton, Yishay Mansour, Michal Moshkovitz:
Partially Interpretable Models with Guarantees on Coverage and Accuracy. ALT 2024: 590-613 - [c302]Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen:
A Theory of Interpretable Approximations. COLT 2024: 648-668 - [c301]Lee Cohen, Yishay Mansour, Shay Moran, Han Shao:
Learnability Gaps of Strategic Classification. COLT 2024: 1223-1259 - [c300]Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran:
The Real Price of Bandit Information in Multiclass Classification. COLT 2024: 1573-1598 - [c299]Orin Levy, Asaf B. Cassel, Alon Cohen, Yishay Mansour:
Eluder-based Regret for Stochastic Contextual MDPs. ICML 2024 - [c298]Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour:
Rate-Optimal Policy Optimization for Linear Markov Decision Processes. ICML 2024 - [c297]Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri:
A Theory of Learning with Competing Objectives and User Feedback. ISAIM 2024: 10-49 - [c296]Marek Eliás, Haim Kaplan, Yishay Mansour, Shay Moran:
Learning-Augmented Algorithms with Explicit Predictors. NeurIPS 2024 - [c295]Liad Erez, Alon Peled-Cohen, Tomer Koren, Yishay Mansour, Shay Moran:
Fast Rates for Bandit PAC Multiclass Classification. NeurIPS 2024 - [c294]Richard Nock, Yishay Mansour:
How to Boost Any Loss Function. NeurIPS 2024 - [i156]Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler:
Principal-Agent Reward Shaping in MDPs. CoRR abs/2401.00298 (2024) - [i155]Lee Cohen, Yishay Mansour, Shay Moran, Han Shao:
Learnability Gaps of Strategic Classification. CoRR abs/2402.19303 (2024) - [i154]Marek Eliás, Haim Kaplan, Yishay Mansour, Shay Moran:
Learning-Augmented Algorithms with Explicit Predictors. CoRR abs/2403.07413 (2024) - [i153]Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran:
The Real Price of Bandit Information in Multiclass Classification. CoRR abs/2405.10027 (2024) - [i152]Edith Cohen, Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer, Eliad Tsfadia:
Data Reconstruction: When You See It and When You Don't. CoRR abs/2405.15753 (2024) - [i151]Yogev Bar-On, Yishay Mansour:
Non-stochastic Bandits With Evolving Observations. CoRR abs/2405.16843 (2024) - [i150]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Rate-Preserving Reductions for Blackwell Approachability. CoRR abs/2406.07585 (2024) - [i149]Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
:
A Theory of Interpretable Approximations. CoRR abs/2406.10529 (2024) - [i148]Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran:
Fast Rates for Bandit PAC Multiclass Classification. CoRR abs/2406.12406 (2024) - [i147]Richard Nock, Yishay Mansour:
How to Boost Any Loss Function. CoRR abs/2407.02279 (2024) - [i146]Ofir Schlisselberg, Ido Cohen, Tal Lancewicki, Yishay Mansour:
Delay as Payoff in MAB. CoRR abs/2408.15158 (2024) - [i145]Asaf B. Cassel, Orin Levy, Yishay Mansour:
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits. CoRR abs/2409.08570 (2024) - [i144]Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer, Nitzan Tur:
On Differentially Private Linear Algebra. CoRR abs/2411.03087 (2024) - [i143]Giannis Fikioris, Robert Kleinberg, Yoav Kolumbus, Raunak Kumar, Yishay Mansour, Éva Tardos:
Learning in Budgeted Auctions with Spacing Objectives. CoRR abs/2411.04843 (2024) - [i142]Idan Barnea, Tal Lancewicki, Yishay Mansour:
Individual Regret in Cooperative Stochastic Multi-Armed Bandits. CoRR abs/2411.06501 (2024) - [i141]Lee Cohen, Yishay Mansour, Shay Moran, Han Shao:
Probably Approximately Precision and Recall Learning. CoRR abs/2411.13029 (2024) - [i140]Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen:
Of Dice and Games: A Theory of Generalized Boosting. CoRR abs/2412.08012 (2024) - 2023
- [c293]Orin Levy, Yishay Mansour:
Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP. AAAI 2023: 8510-8517 - [c292]Eitan-Hai Mashiah, Idan Attias, Yishay Mansour:
Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers. AAAI 2023: 9090-9098 - [c291]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. ALT 2023: 471-509 - [c290]Yogev Bar-On, Yishay Mansour:
Uniswap Liquidity Provision: An Online Learning Approach. FC Workshops 2023: 247-261 - [c289]Christoph Dann, Yishay Mansour, Mehryar Mohri:
Reinforcement Learning Can Be More Efficient with Multiple Rewards. ICML 2023: 6948-6967 - [c288]Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, Yishay Mansour:
Regret Minimization and Convergence to Equilibria in General-sum Markov Games. ICML 2023: 9343-9373 - [c287]Orin Levy, Alon Cohen, Asaf B. Cassel, Yishay Mansour:
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation. ICML 2023: 19287-19314 - [c286]Yishay Mansour, Richard Nock, Robert C. Williamson:
Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice. ICML 2023: 23706-23742 - [c285]Uri Sherman, Tomer Koren, Yishay Mansour:
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation. ICML 2023: 31117-31150 - [c284]Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer:
Concurrent Shuffle Differential Privacy Under Continual Observation. ICML 2023: 33961-33982 - [c283]Lee Cohen, Yishay Mansour, Michal Moshkovitz:
Finding Safe Zones of Markov Decision Processes Policies. NeurIPS 2023 - [c282]Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran:
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. NeurIPS 2023 - [c281]Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer:
Black-Box Differential Privacy for Interactive ML. NeurIPS 2023 - [c280]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. NeurIPS 2023 - [i139]Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer:
Concurrent Shuffle Differential Privacy Under Continual Observation. CoRR abs/2301.12535 (2023) - [i138]Uri Sherman, Tomer Koren, Yishay Mansour:
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation. CoRR abs/2301.13087 (2023) - [i137]Yogev Bar-On, Yishay Mansour:
Uniswap Liquidity Provision: An Online Learning Approach. CoRR abs/2302.00610 (2023) - [i136]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. CoRR abs/2302.01517 (2023) - [i135]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) - [i134]Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer:
On Differentially Private Online Predictions. CoRR abs/2302.14099 (2023) - [i133]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) - [i132]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) - [i131]Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran:
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. CoRR abs/2307.00642 (2023) - [i130]Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour:
Rate-Optimal Policy Optimization for Linear Markov Decision Processes. CoRR abs/2308.14642 (2023) - [i129]Yogev Bar-On, Yishay Mansour:
Optimal Publishing Strategies on a Base Layer. CoRR abs/2312.06448 (2023) - [i128]Aadirupa Saha, Vitaly Feldman, Tomer Koren, Yishay Mansour:
Faster Convergence with Multiway Preferences. CoRR abs/2312.11788 (2023) - 2022
- [j113]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) - [j112]Noa Ecker, Dana Azouri, Ben Bettisworth, Alexandros Stamatakis, Yishay Mansour, Itay Mayrose, Tal Pupko:
A LASSO-based approach to sample sites for phylogenetic tree search. Bioinform. 38(Supplement_1): i118-i124 (2022) - [j111]Yishay Mansour, Alex Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu:
Bayesian Exploration: Incentivizing Exploration in Bayesian Games. Oper. Res. 70(2): 1105-1127 (2022) - [j110]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) - [j109]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved Generalization Bounds for Adversarially Robust Learning. J. Mach. Learn. Res. 23: 175:1-175:31 (2022) - [j108]Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour:
Nonstochastic Bandits with Composite Anonymous Feedback. J. Mach. Learn. Res. 23: 277:1-277:24 (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: