Ammar, Haitham Bou

19 publications

ICLR 2025 Efficient Reinforcement Learning with Large Language Model Priors Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou Ammar, Jun Wang

ICLRW 2025 Hierarchical Episodic Memory in LLMs via Multi-Scale Event Organization Martin Benfeghoul, Haitham Bou Ammar, Jun Wang, Zafeirios Fountas

ICLR 2025 Human-Inspired Episodic Memory for Infinite Context LLMs Zafeirios Fountas, Martin Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou Ammar, Jun Wang

ICLR 2025 Mixture of Attentions for Speculative Decoding Matthieu Zimmer, Milan Gritta, Gerasimos Lampouras, Haitham Bou Ammar, Jun Wang

ICLRW 2024 Bayesian Reward Models for LLM Alignment Adam X. Yang, Maxime Robeyns, Thomas Coste, Jun Wang, Haitham Bou Ammar, Laurence Aitchison

ICMLW 2024 Bayesian Reward Models for LLM Alignment Adam X. Yang, Maxime Robeyns, Thomas Coste, Zhengyan Shi, Jun Wang, Haitham Bou Ammar, Laurence Aitchison

NeurIPS 2024 Group Robust Preference Optimization in Reward-Free RLHF Shyam Sundhar Ramesh, Yifan Hu, Iason Chaimalas, Viraj Mehta, Pier Giuseppe Sessa, Haitham Bou Ammar, Ilija Bogunovic

NeurIPS 2023 End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou Ammar

NeurIPS 2023 Framework and Benchmarks for Combinatorial and Mixed-Variable Bayesian Optimization Kamil Dreczkowski, Antoine Grosnit, Haitham Bou Ammar

NeurIPS 2023 Online PCA in Converging Self-Consistent Field Equations Xihan Li, Xiang Chen, Rasul Tutunov, Haitham Bou Ammar, Lei Wang, Jun Wang

NeurIPS 2022 Enhancing Safe Exploration Using Safety State Augmentation Aivar Sootla, Alexander Cowen-Rivers, Jun Wang, Haitham Bou Ammar

TMLR 2022 Online Double Oracle Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez-Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou Ammar, Yaodong Yang

NeurIPS 2022 Optimistic Tree Searches for Combinatorial Black-Box Optimization Cedric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou Ammar, Jun Wang

ICLR 2022 Reinforcement Learning in Presence of Discrete Markovian Context Evolution Hang Ren, Aivar Sootla, Taher Jafferjee, Junxiao Shen, Jun Wang, Haitham Bou Ammar

CoRL 2021 Robot Reinforcement Learning on the Constraint Manifold Puze Liu, Davide Tateo, Haitham Bou Ammar, Jan Peters

NeurIPS 2019 Multi-View Reinforcement Learning Minne Li, Lisheng Wu, Jun Wang, Haitham Bou Ammar

NeurIPS 2018 Distributed Multitask Reinforcement Learning with Quadratic Convergence Rasul Tutunov, Dongho Kim, Haitham Bou Ammar

ICML 2015 Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret Haitham Bou Ammar, Rasul Tutunov, Eric Eaton

ICML 2014 Online Multi-Task Learning for Policy Gradient Methods Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, Matthew Taylor