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Shie Mannor

Prof.

 https://orcid.org/0000-0003-4439-7647
    20012025

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    • 2024

      Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel

      Gadot, U., Wang, K., Kumar, N., Levy, K. Y. & Mannor, S., 2024, In: Proceedings of Machine Learning Research. 235, p. 14408-14432 25 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Efficient Value Iteration for s-rectangular Robust Markov Decision Processes

      Kumar, N., Wang, K., Levy, K. & Mannor, S., 2024, In: Proceedings of Machine Learning Research. 235, p. 25682-25725 44 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization

      Du, Y., Winnicki, A., Dalal, G., Mannor, S. & Srikant, R., 2024, In: Proceedings of Machine Learning Research. 235, p. 11830-11887 58 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Improving Token-Based World Models with Parallel Observation Prediction

      Cohen, L., Wang, K., Kang, B. & Mannor, S., 2024, In: Proceedings of Machine Learning Research. 235, p. 9138-9160 23 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Prospective Side Information for Latent MDPs

      Kwon, J., Efroni, Y., Mannor, S. & Caramanis, C., 2024, In: Proceedings of Machine Learning Research. 235, p. 25755-25783 29 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Sobolev Space Regularised Pre Density Models

      Kozdoba, M., Perets, B. & Mannor, S., 2024, In: Proceedings of Machine Learning Research. 235, p. 25494-25533 40 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Solving Non-rectangular Reward-Robust MDPs via Frequency Regularization

      Gadot, U., Derman, E., Kumar, N., Elfatihi, M., Levy, K. & Mannor, S., 25 Mar 2024, In: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 19, p. 2109021098 1 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2023

      DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles

      Karkus, P., Ivanovic, B., Mannor, S. & Pavone, M., 2023, In: Proceedings of Machine Learning Research. 205, p. 2170-2180 11 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Individualized Dosing Dynamics via Neural Eigen Decomposition

      Belogolovsky, S., Greenberg, I., Eytan, D. & Mannor, S., 2023, In: Advances in Neural Information Processing Systems. 36, p. 56211-56233 23 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Learning Hidden Markov Models When the Locations of Missing Observations are Unknown

      Perets, B., Kozdoba, M. & Mannor, S., 2023, In: Proceedings of Machine Learning Research. 202, p. 27642-27667 26 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Learning to Initiate and Reason in Event-Driven Cascading Processes

      Atzmon, Y., Meirom, E. A., Mannor, S. & Chechik, G., 2023, In: Proceedings of Machine Learning Research. 202, p. 1218-1243 26 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning

      Khanna, P., Tennenholtz, G., Merlis, N., Mannor, S. & Tessler, C., 2023, In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. 2023-May, p. 2430-2432 3 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Policy Gradient for Rectangular Robust Markov Decision Processes

      Kumar, N., Geist, M., Levy, K., Derman, E. & Mannor, S., 2023, In: Advances in Neural Information Processing Systems. 36

      Research output: Contribution to journal › Conference article › peer-review

    • PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient

      Wang, K., Zhou, D., Feng, J. & Mannor, S., 2023, In: Proceedings of Machine Learning Research. 202, p. 36694-36713 20 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Representation-Driven Reinforcement Learning

      Nabati, O., Tennenholtz, G. & Mannor, S., 2023, In: Proceedings of Machine Learning Research. 202, p. 25588-25603 16 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Reward-Mixing MDPs with Few Latent Contexts are Learnable

      Kwon, J., Efroni, Y., Caramanis, C. & Mannor, S., 2023, In: Proceedings of Machine Learning Research. 202, p. 18057-18082 26 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Train Hard, Fight Easy: Robust Meta Reinforcement Learning

      Greenberg, I., Chechik, G., Mannor, S. & Meirom, E., 2023, In: Advances in Neural Information Processing Systems. 36

      Research output: Contribution to journal › Conference article › peer-review

    • 2022

      Actor-Critic based Improper Reinforcement Learning

      Zaki, M., Mohan, A., Gopalan, A. & Mannor, S., 2022, In: Proceedings of Machine Learning Research. 162, p. 25867-25919 53 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Analysis of Stochastic Processes through Replay Buffers

      Di Castro Shashua, S., Mannor, S. & Di Castro, D., 2022, In: Proceedings of Machine Learning Research. 162, p. 5039-5060 22 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms

      Kwon, J., Efroni, Y., Caramanis, C. & Mannor, S., 2022, In: Proceedings of Machine Learning Research. 162, p. 11772-11789 18 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Improper Reinforcement Learning with Gradient-based Policy Optimization

      Zaki, M., Mohan, A., Gopalan, A. & Mannor, S., 2022, In: International Conference on Machine Learning.

      Research output: Contribution to journal › Conference article › peer-review

    • Optimizing Tensor Network Contraction Using Reinforcement Learning

      Merom, E., Maron, H., Mannor, S. & Chechick, G., 2022, In: Proceedings of Machine Learning Research. 162, p. 15278-15292 15 p.

      Research output: Contribution to journal › Conference article › peer-review

    • The Geometry of Robust Value Functions

      Wang, K., Kumar, N., Zhou, K., Hooi, B., Feng, J. & Mannor, S., 2022, In: Proceedings of Machine Learning Research. 162, p. 22727-22751 25 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2021

      Action Redundancy in Reinforcement Learning

      Baram, N., Tennenholtz, G. & Mannor, S., 2021, In: Proceedings of Machine Learning Research. 161, p. 376-385 10 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Bandits with Partially Observable Confounded Data

      Tennenholtz, G., Shalit, U., Mannor, S. & Efroni, Y., 2021, In: Proceedings of Machine Learning Research. 161, p. 430-439 10 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Known Unknowns: Learning Novel Concepts Using Reasoning-by-Elimination

      Agrawal, H., Meirom, E. A., Atzmon, Y., Mannor, S. & Chechik, G., 2021, In: Proceedings of Machine Learning Research. 161, p. 504-514 11 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2020

      An adaptive stochastic optimization algorithm for resource allocation

      Fontaine, X., Mannor, S. & Perchet, V., 2020, In: Proceedings of Machine Learning Research. 117, p. 319-363 45 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Online planning with lookahead policies

      Efroni, Y., Ghavamzadeh, M. & Mannor, S., 2020, In: Advances in Neural Information Processing Systems. 2020-December

      Research output: Contribution to journal › Conference article › peer-review

    • Tight Lower Bounds for Combinatorial Multi-Armed Bandits

      Merlis, N. & Mannor, S., 2020, In: Proceedings of Machine Learning Research. 125, p. 2830-2857 28 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2019

      A Bayesian Approach to Robust Reinforcement Learning

      Derman, E., Mankowitz, D., Mann, T. & Mannor, S., 2019, In: Proceedings of Machine Learning Research. 115, p. 648-658 11 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem

      Merlis, N. & Mannor, S., 2019, In: Proceedings of Machine Learning Research. 99, p. 2465-2489 25 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Distributional policy optimization: An alternative approach for continuous control

      Tessler, C., Tennenholtz, G. & Mannor, S., 2019, In: Advances in Neural Information Processing Systems. 32

      Research output: Contribution to journal › Conference article › peer-review

    • Tight regret bounds for model-based reinforcement learning with greedy policies

      Efroni, Y., Merlis, N., Ghavamzadeh, M. & Mannor, S., 2019, In: Advances in Neural Information Processing Systems. 32

      Research output: Contribution to journal › Conference article › peer-review

    • Value propagation for decentralized networked deep multi-agent reinforcement learning

      Qu, C., Mannor, S., Xu, H., Qi, Y., Song, L. & Xiong, J., 2019, In: Advances in Neural Information Processing Systems. 32

      Research output: Contribution to journal › Conference article › peer-review

    • 2018

      A General Approach to Multi-Armed Bandits Under Risk Criteria

      Cassel, A., Mannor, S. & Zeevi, A., 2018, In: Proceedings of Machine Learning Research. 75, p. 1295-1306 12 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning

      Dalal, G., Szörényi, B., Thoppe, G. & Mannor, S., 2018, In: Proceedings of Machine Learning Research. 75, p. 1199-1233 35 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Learn what not to learn: Action elimination with deep reinforcement learning

      Zahavy, T., Haroush, M., Merlis, N., Mankowitz, D. J. & Mannor, S., 2018, In: Advances in Neural Information Processing Systems. 2018-December, p. 3562-3573 12 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Multiple-step greedy policies in online and approximate reinforcement learning

      Efroni, Y., Scherrer, B., Dalal, G. & Mannor, S., 2018, In: Advances in Neural Information Processing Systems. 2018-December, p. 5238-5247 10 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2017

      Rotting bandits

      Levine, N., Crammer, K. & Mannor, S., 2017, In: Advances in Neural Information Processing Systems. 2017-December, p. 3075-3084 10 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Shallow updates for deep reinforcement learning

      Levine, N., Zahavy, T., Mankowitz, D. J., Tamar, A. & Mannor, S., 2017, In: Advances in Neural Information Processing Systems. 2017-December, p. 3136-3146 11 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2016

      Adaptive skills adaptive partitions (ASAP)

      Mankowitz, D. J., Mann, T. A. & Mannor, S., 2016, In: Advances in Neural Information Processing Systems. p. 1596-1604 9 p.

      Research output: Contribution to journal › Conference article › peer-review

    • 2015

      Community detection via measure space embedding

      Kozdoba, M. & Mannor, S., 2015, In: Advances in Neural Information Processing Systems. 2015-January, p. 2890-2898 9 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Localized epidemic detection in networks with overwhelming noise

      Meirom, E. A., Milling, C., Caramanis, C., Mannor, S., Shakkottai, S. & Orda, A., 24 Jun 2015, In: Performance Evaluation Review. 43, 1, p. 441-442 2 p.

      Research output: Contribution to journal › Conference article › peer-review

      Open Access

    • Online learning for adversaries with memory: Price of past mistakes

      Anava, O., Hazan, E. & Mannor, S., 2015, In: Advances in Neural Information Processing Systems. 2015-January, p. 784-792 9 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Policy gradient for coherent risk measures

      Tamar, A., Chow, Y., Ghavamzadeh, M. & Mannor, S., 2015, In: Advances in Neural Information Processing Systems. 2015-January, p. 1468-1476 9 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Risk-sensitive and robust decision-making: A CVaR optimization approach

      Chow, Y., Tamar, A., Mannor, S. & Pavone, M., 2015, In: Advances in Neural Information Processing Systems. 2015-January, p. 1522-1530 9 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Sensor selection for crowdsensing dynamical systems

      Schnitzler, F., Yuan, J. & Mannor, S., 2015, In: Journal of Machine Learning Research. 38, p. 829-837 9 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Thompson sampling for learning parameterized markov decision processes

      Gopalan, A. & Mannor, S., 2015, In: Journal of Machine Learning Research. 40, 2015

      Research output: Contribution to journal › Conference article › peer-review

    • 2014

      Approachability in unknown games: Online learning meets multi-objective optimization

      Mannor, S., Perchet, V. & Stoltz, G., 2014, In: Journal of Machine Learning Research. 35, p. 339-355 17 p.

      Research output: Contribution to journal › Conference article › peer-review

    • Combining a gauss-markov model and gaussian process for traffic prediction in dublin city center

      Schnitzler, F., Liebig, T., Mannor, S. & Morik, K., 2014, In: CEUR Workshop Proceedings. 1133, p. 373-374 2 p.

      Research output: Contribution to journal › Conference article › peer-review