Guy Tennenholtz

According to our database¹, Guy Tennenholtz authored at least 31 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2024

Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators.

[BibT_eX]

[DOI]

Ori Linial

Guy Tennenholtz

Uri Shalit

CoRR, 2024

Embedding-Aligned Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Bayesian Regret Minimization in Offline Bandits.

[BibT_eX]

[DOI]

Marek Petrik

Guy Tennenholtz

Mohammad Ghavamzadeh

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Demystifying Embedding Spaces using Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization.

[BibT_eX]

[DOI]

Craig Boutilier

Martin Mladenov

Guy Tennenholtz

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation.

[BibT_eX]

[DOI]

CoRR, 2023

Factual and Personalized Recommendations using Language Models and Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models.

[BibT_eX]

[DOI]

Craig Boutilier

Martin Mladenov

Guy Tennenholtz

CoRR, 2023

A Convex Relaxation Approach to Bayesian Regret Minimization in Offline Bandits.

[BibT_eX]

[DOI]

Mohammad Ghavamzadeh

Marek Petrik

Guy Tennenholtz

CoRR, 2023

Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics.

[BibT_eX]

[DOI]

CoRR, 2023

Reinforcement Learning with History Dependent Dynamic Contexts.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Representation-Driven Reinforcement Learning.

[BibT_eX]

[DOI]

Ofir Nabati

Guy Tennenholtz

Shie Mannor

Proceedings of the International Conference on Machine Learning, 2023

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

[BibT_eX]

[DOI]

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Reinforcement Learning with a Terminator.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Guy Tennenholtz

Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Roy Zohar

Shie Mannor

Guy Tennenholtz

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Maximum Entropy Reinforcement Learning with Mixture Policies.

[BibT_eX]

[DOI]

Nir Baram

Guy Tennenholtz

Shie Mannor

CoRR, 2021

GELATO: Geometrically Enriched Latent Model for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Guy Tennenholtz

Nir Baram

Shie Mannor

CoRR, 2021

Bandits with partially observable confounded data.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Action redundancy in reinforcement learning.

[BibT_eX]

[DOI]

Nir Baram

Guy Tennenholtz

Shie Mannor

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

The Pendulum Arrangement: Maximizing the Escape Time of Heterogeneous Random Walks.

[BibT_eX]

[DOI]

Asaf B. Cassel

Shie Mannor

Guy Tennenholtz

CoRR, 2020

Bandits with Partially Observable Offline Data.

[BibT_eX]

[DOI]

CoRR, 2020

Off-Policy Evaluation in Partially Observable Environments.

[BibT_eX]

[DOI]

Guy Tennenholtz

Uri Shalit

Shie Mannor

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Natural Language State Representation for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Distributional Policy Optimization: An Alternative Approach for Continuous Control.

[BibT_eX]

[DOI]

Chen Tessler

Guy Tennenholtz

Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The Natural Language of Actions.

[BibT_eX]

[DOI]

Guy Tennenholtz

Shie Mannor

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Train on Validation: Squeezing the Data Lemon.

[BibT_eX]

[DOI]

Guy Tennenholtz

Tom Zahavy

Shie Mannor

CoRR, 2018

2017

The Stochastic Firefighter Problem.

[BibT_eX]

[DOI]

Guy Tennenholtz

Constantine Caramanis

Shie Mannor

CoRR, 2017

Guy Tennenholtz

Timeline

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