Guy Tennenholtz
Guy Tennenholtz is a research scientist at Google Research. He received his Ph.D. from the Technion Institute of Technology in 2022. He has published over 20 papers in major machine learning conferences. His research focuses include reinforcement learning and causal inference with applications in ecosystems in recommender systems, healthcare, and robotics.
Authored Publications
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Factual and Personalized Recommendation Language Modeling with Reinforcement Learning
Jihwan Jeong
Mohammad Ghavamzadeh
Proceedings of the First Conference on Language Modeling (COLM-24), Philadelphia (2024)
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta Reinforcement Learning
Anthony Liang
Erdem Biyik
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS-24), Vancouver (2024)
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
Alizée Pace
Hugo Yèche
Bernhard Schölkopf
Gunnar Rätsch
The Twelfth International Conference on Learning Representations (2024)
Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models
Martin Mladenov
Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver (2024) (to appear)
Embedding-Aligned Language Models
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS-24), Vancouver (2024)
Demystifying Embedding Spaces using Large Language Models
Jihwan Jeong
Lior Shani
Martin Mladenov
The Twelfth International Conference on Learning Representations (2024)
Reinforcement Learning with History Dependent Dynamic Contexts
Nadav Merlis
Martin Mladenov
Proceedings of the 40th International Conference on Machine Learning (ICML 2023), Honolulu, Hawaii
Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation
Li Ding
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World (2023)
