Guy Tennenholtz

According to our database, Guy Tennenholtz authored at least 28 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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

Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier

CoRR, 2024

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

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.

Li Ding, Masrour Zoghi, Guy Tennenholtz, Maryam Karimzadehgan

CoRR, 2023

Factual and Personalized Recommendations using Language Models and Reinforcement Learning.

Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2023

Demystifying Embedding Spaces using Large Language Models.

Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier

CoRR, 2023

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

Craig Boutilier, Martin Mladenov, Guy Tennenholtz

CoRR, 2023

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

Mohammad Ghavamzadeh, Marek Petrik, Guy Tennenholtz

CoRR, 2023

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding.

Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz

CoRR, 2023

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

Guy Tennenholtz, Martin Mladenov, Nadav Merlis, Craig Boutilier

CoRR, 2023

Reinforcement Learning with History Dependent Dynamic Contexts.

Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier

Proceedings of the International Conference on Machine Learning, 2023

Representation-Driven Reinforcement Learning.

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.

Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler

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

2022

Reinforcement Learning with a Terminator.

Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal

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.

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.

Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

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.

Nir Baram, Guy Tennenholtz, Shie Mannor

CoRR, 2021

GELATO: Geometrically Enriched Latent Model for Offline Reinforcement Learning.

Guy Tennenholtz, Nir Baram, Shie Mannor

CoRR, 2021

Bandits with partially observable confounded data.

Guy Tennenholtz, Uri Shalit, Shie Mannor, Yonathan Efroni

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

Action redundancy in reinforcement learning.

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.

Asaf B. Cassel, Shie Mannor, Guy Tennenholtz

CoRR, 2020

Bandits with Partially Observable Offline Data.

Guy Tennenholtz, Uri Shalit, Shie Mannor, Yonathan Efroni

CoRR, 2020

Off-Policy Evaluation in Partially Observable Environments.

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.

Erez Schwartz, Guy Tennenholtz, Chen Tessler, Shie Mannor

CoRR, 2019

Distributional Policy Optimization: An Alternative Approach for Continuous Control.

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.

Guy Tennenholtz, Shie Mannor

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

2018

Train on Validation: Squeezing the Data Lemon.

Guy Tennenholtz, Tom Zahavy, Shie Mannor

CoRR, 2018

2017

The Stochastic Firefighter Problem.

Guy Tennenholtz, Constantine Caramanis, Shie Mannor

CoRR, 2017