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Guy Tennenholtz
Guy Tennenholtz
Research Scientist, Google Research
Geverifieerd e-mailadres voor google.com
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Off-policy evaluation in partially observable environments
G Tennenholtz, U Shalit, S Mannor
Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10276 …, 2020
912020
The Natural Language of Actions
G Tennenholtz, S Mannor
Proceedings of the 36th International Conference on Machine Learning, 2019
672019
Distributional policy optimization: An alternative approach for continuous control
C Tessler*, G Tennenholtz*, S Mannor
Advances in Neural Information Processing Systems 32, 1352--1362, 2019
542019
Bandits with Partially Observable Confounded Data
G Tennenholtz, U Shalit, S Mannor, Y Efroni
Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence …, 2021
34*2021
Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning
G Tennenholtz, S Mannor
Advances in Neural Information Processing Systems, 2022
21*2022
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning
G Tennenholtz, A Hallak, G Dalal, S Mannor, G Chechik, U Shalit
International Conference on Learning Representations, 2022
182022
Demystifying Embedding Spaces using Large Language Models
G Tennenholtz, Y Chow, CW Hsu, J Jeong, L Shani, A Tulepbergenov, ...
The Twelfth International Conference on Learning Representations, 2024
162024
Train on validation: squeezing the data lemon
G Tennenholtz, T Zahavy, S Mannor
arXiv preprint arXiv:1802.05846, 2018
152018
Language is power: Representing states using natural language in reinforcement learning
E Schwartz, G Tennenholtz, C Tessler, S Mannor
arXiv preprint arXiv:1910.02789, 2019
132019
Natural contrast enhancement for dichromats using similarity maps
G Tennenholtz, I Zachevsky
2016 IEEE International Conference on the Science of Electrical Engineering …, 2016
122016
Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning
R Zohar, S Mannor, G Tennenholtz
Proceedings of the AAAI Conference on Artificial Intelligence 36, 2022
112022
Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization
C Boutilier, M Mladenov, G Tennenholtz
Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 22575 …, 2024
10*2024
Development of a ToF pixel with VOD shutter mechanism, high IR QE, four storages, and CDS
E Tadmor, D Cohen, G Yahav, G Tennenholtz, G Lehana, A Lahav, ...
IEEE Transactions on Electron Devices 63 (7), 2892-2899, 2016
102016
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
A Pace, H Yèche, B Schölkopf, G Rätsch, G Tennenholtz
The Twelfth International Conference on Learning Representations, 2024
82024
Action Redundancy in Reinforcement Learning
N Baram*, G Tennenholtz*, S Mannor
Proceedings of the 37th Conference on Uncertainty in Artificial …, 2021
82021
Sequential vaccination for containing epidemics
G Tennenholtz, C Caramanis, S Mannor
medRxiv, 2020.04. 13.20060269, 2020
62020
Inference-aware fine-tuning for best-of-n sampling in large language models
Y Chow, G Tennenholtz, I Gur, V Zhuang, B Dai, S Thiagarajan, ...
arXiv preprint arXiv:2412.15287, 2024
52024
Reinforcement Learning with History-Dependent Dynamic Contexts
G Tennenholtz, N Merlis, L Shani, M Mladenov, C Boutilier
Proceedings of the 40th International Conference on Machine Learning, 2023
52023
Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning
P Khanna, G Tennenholtz, N Merlis, S Mannor, C Tessler
The 22nd International Conference on Autonomous Agents and Multiagent …, 2023
4*2023
Reinforcement Learning with a Terminator
G Tennenholtz, N Merlis, L Shani, S Mannor, U Shalit, G Chechik, ...
Advances in Neural Information Processing Systems, 2022
42022
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