Haitham Bou-Ammar

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Rasul TutunovMassachusetts Institute of TechnologyVerified email at mit.edu
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
Karl TuylsResearch Scientist, Entrepreneur, ex-Google DeepMind, Prof at University of LiverpoolVerified email at hcompany.ai
Gerhard WeissProfessor of Computer Science and Artificial Intelligence, Maastricht UniversityVerified email at maastrichtuniversity.nl
Antoine GrosnitResearch Scientist, Noah's Ark lab, LondonVerified email at huawei.com
Alexander I. Cowen-RiversDeepMindVerified email at deepmind.com
Matthew E. TaylorProfessor, University of AlbertaVerified email at ualberta.ca
Eric EatonUniversity of PennsylvaniaVerified email at cis.upenn.edu
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
Decebal Constantin MocanuAssociate Professor in Machine Learning, University of Luxembourg, TU EindhovenVerified email at uni.lu
Kurt DriessensAssociate Professor, Maastricht UniversityVerified email at maastrichtuniversity.nl
Alexandre MaravalHuawei R&D UKVerified email at huawei.com
Siqi ChenTianjin UniversityVerified email at tju.edu.cn
Felix LeibfriedEisler CapitalVerified email at eislercapital.com
Ryan-Rhys GriffithsFutureHouseVerified email at futurehouse.org
Antonio LiottaProfessor at Faculty of Engineering, University of Bozen-Bolzano, ItalyVerified email at unibz.it
Ali JadbabaieJR East Professor of Engineering, MITVerified email at mit.edu
Bijan Ranjbar-SahraeiFreelance Data ScientistVerified email at mydataexpert.nl
Yaodong YangBOYA (博雅) Assistant Professor at Peking UniversityVerified email at pku.edu.cn
Holger VoosUniversity of Luxembourg, SnT Automation & Robotics Research GroupVerified email at uni.lu

Haitham Bou-Ammar

RL-Team Leader, BO-Team Leader, MAS-Team Leader @ Huawei London & H. Assistant Professor @ UCL

Verified email at huawei.com

Machine Learning Reinforcement Learning Optimisation Variational Inference


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Smarts: An open-source scalable multi-agent rl training school for autonomous driving M Zhou, J Luo, J Villella, Y Yang, D Rusu, J Miao, W Zhang, M Alban, ... Conference on robot learning, 264-285, 2021	215	2021
Online multi-task learning for policy gradient methods HB Ammar, E Eaton, P Ruvolo, M Taylor International conference on machine learning, 1206-1214, 2014	193	2014
Hebo: Pushing the limits of sample-efficient hyper-parameter optimisation AI Cowen-Rivers, W Lyu, R Tutunov, Z Wang, A Grosnit, RR Griffiths, ... Journal of Artificial Intelligence Research 74, 1269-1349, 2022	174*	2022
Controller design for quadrotor uavs using reinforcement learning H Bou-Ammar, H Voos, W Ertel 2010 IEEE international conference on control applications, 2130-2135, 2010	131	2010
An automated measure of mdp similarity for transfer in reinforcement learning HB Ammar, E Eaton, ME Taylor, DC Mocanu, K Driessens, G Weiss, ... 28th AAAI Conference on Artificial Intelligence, AAAI 2014, 31-37, 2014	115	2014
Autonomous cross-domain knowledge transfer in lifelong policy gradient reinforcement learning HB Ammar, E Eaton, JM Luna, P Ruvolo Twenty-fourth international joint conference on artificial intelligence, 2015	104	2015
Wasserstein robust reinforcement learning MA Abdullah, H Ren, HB Ammar, V Milenkovic, R Luo, M Zhang, J Wang arXiv preprint arXiv:1907.13196, 2019	100	2019
Unsupervised cross-domain transfer in policy gradient reinforcement learning via manifold alignment HB Ammar, E Eaton, P Ruvolo, M Taylor Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	98	2015
Safe policy search for lifelong reinforcement learning with sublinear regret HB Ammar, R Tutunov, E Eaton International Conference on Machine Learning, 2361-2369, 2015	82	2015
Reinforcement learning transfer via sparse coding HB Ammar, K Tuyls, ME Taylor, K Driessens, G Weiss Proceedings of the 11th international conference on autonomous agents and …, 2012	79	2012
Distributed newton method for large-scale consensus optimization R Tutunov, H Bou-Ammar, A Jadbabaie IEEE Transactions on Automatic Control 64 (10), 3983-3994, 2019	74	2019
Sauté rl: Almost surely safe reinforcement learning using state augmentation A Sootla, AI Cowen-Rivers, T Jafferjee, Z Wang, DH Mguni, J Wang, ... International Conference on Machine Learning, 20423-20443, 2022	67	2022
Theoretically-grounded policy advice from multiple teachers in reinforcement learning settings with applications to negative transfer Y Zhan, HB Ammar arXiv preprint arXiv:1604.03986, 2016	67	2016
High-dimensional Bayesian optimisation with variational autoencoders and deep metric learning A Grosnit, R Tutunov, AM Maraval, RR Griffiths, AI Cowen-Rivers, L Yang, ... arXiv preprint arXiv:2106.03609, 2021	61	2021
Evolution of cooperation in arbitrary complex networks B Ranjbar-Sahraei, H Bou Ammar, D Bloembergen, K Tuyls, G Weiss Proceedings of the 2014 international conference on Autonomous agents and …, 2014	59	2014
Balancing two-player stochastic games with soft q-learning J Grau-Moya, F Leibfried, H Bou-Ammar arXiv preprint arXiv:1802.03216, 2018	58	2018
Toward real-world automated antibody design with combinatorial Bayesian optimization A Khan, AI Cowen-Rivers, A Grosnit, PA Robert, V Greiff, E Smorodina, ... Cell Reports Methods 3 (1), 2023	55*	2023
Nonlinear tracking and landing controller for quadrotor aerial robots H Voos, H Bou-Ammar Control Applications (CCA), 2010 IEEE International Conference on, 2136-2141, 2010	52	2010
Robot reinforcement learning on the constraint manifold P Liu, D Tateo, HB Ammar, J Peters Conference on Robot Learning, 1357-1366, 2022	48	2022
Factored four way conditional restricted boltzmann machines for activity recognition DC Mocanu, HB Ammar, D Lowet, K Driessens, A Liotta, G Weiss, K Tuyls Pattern Recognition Letters 66, 100-108, 2015	48	2015

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