Guy Tennenholtz
20 papers · 2019–2026 · 6 conferences · across top CS/AI conferences
Achievements
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π Renaissance Researcher (6) π Interdisciplinary Bridge π Conference Polyglot (5) π Academic Marathon (6) πΊοΈ Taxonomy Completionist (29)
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Conference Polyglot
(5)
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Academic Marathon
(6)
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Keyword Pioneer
π€
Dynamic Duo
(10)
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Triple Crown
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Grand Slam
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Unstoppable
(7)
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Keyword Collector
(64)
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Century Club
(19)
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Prolific Year
(6)
Conferences
ICML (5)
NIPS (5)
ICLR (4)
AAAI (3)
UAI (2)
EACL (1)
Top co-authors
Keywords
reinforcement learning
(7)
regret bound
(3)
contextual bandit
(3)
model-based reinforcement learning
(3)
generative model
(2)
policy gradient
(2)
markov decision process
(2)
policy optimization
(1)
sequential decision making
(1)
online learning
(1)
embedding learning
(1)
autonomous driving
(1)
mechanism design
(1)
behavior cloning
(1)
function approximation
(1)
offline reinforcement learning
(1)
partially observable markov decision process
(1)
feature space
(1)
continuous control
(1)
temporal dynamics
(1)
Papers
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
EACL 2026
Preference Adaptive and Sequential Text-to-Image Generation
ICML 2025
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
ICLR 2025
Demystifying Embedding Spaces using Large Language Models
ICLR 2024
Embedding-Aligned Language Models
NIPS 2024
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
NIPS 2024
Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization
AAAI 2024
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
ICLR 2024
Bayesian Regret Minimization in Offline Bandits
ICML 2024
Representation-Driven Reinforcement Learning
ICML 2023
Reinforcement Learning with History Dependent Dynamic Contexts
ICML 2023
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning
ICLR 2022
Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning
NIPS 2022
Reinforcement Learning with a Terminator
NIPS 2022
Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning
AAAI 2022
Bandits with partially observable confounded data
UAI 2021
Action redundancy in reinforcement learning
UAI 2021
Off-Policy Evaluation in Partially Observable Environments
AAAI 2020
The Natural Language of Actions
ICML 2019
Distributional Policy Optimization: An Alternative Approach for Continuous Control
NIPS 2019