Haitham Bou-Ammar

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Rasul TutunovMassachusetts Institute of TechnologyEmail confirmado em mit.edu
Jun WangProfessor, Computer Science, University College LondonEmail confirmado em cs.ucl.ac.uk
Karl TuylsResearch Scientist Meta AI, ex-Google DeepMind, Prof at University of LiverpoolEmail confirmado em meta.com
Gerhard WeissProfessor of Computer Science and Artificial Intelligence, Maastricht UniversityEmail confirmado em maastrichtuniversity.nl
Antoine GrosnitResearch Scientist, Noah's Ark lab, LondonEmail confirmado em huawei.com
Alexander I. Cowen-RiversDeepMindEmail confirmado em deepmind.com
Matthew E. TaylorProfessor, University of AlbertaEmail confirmado em ualberta.ca
Eric EatonUniversity of PennsylvaniaEmail confirmado em cis.upenn.edu
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIEmail confirmado em ias.tu-darmstadt.de
Decebal Constantin MocanuAssociate Professor in Machine Learning, University of Luxembourg, TU EindhovenEmail confirmado em uni.lu
Aivar Sootlaresearch associateEmail confirmado em eng.ox.ac.uk
Kurt DriessensAssociate Professor, Maastricht UniversityEmail confirmado em maastrichtuniversity.nl
Alexandre MaravalHuawei R&D UKEmail confirmado em huawei.com
Siqi ChenTianjin UniversityEmail confirmado em tju.edu.cn
Ali JadbabaieJR East Professor of Engineering, MITEmail confirmado em mit.edu
Antonio LiottaProfessor at Faculty of Engineering, University of Bozen-Bolzano, ItalyEmail confirmado em unibz.it
Bijan Ranjbar-SahraeiFreelance Data ScientistEmail confirmado em mydataexpert.nl
Ryan-Rhys GriffithsFutureHouse | University of CambridgeEmail confirmado em futurehouse.org
Davide TateoResearch group leader at Technische Universität DarmstadtEmail confirmado em ias.informatik.tu-darmstadt.de
Puze LiuGerman Research Center for AI (DFKI)Email confirmado em dfki.de

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Haitham Bou-Ammar

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

Email confirmado em huawei.com

Machine Learning Reinforcement Learning Optimisation Variational Inference


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
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	237	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	198	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	191*	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	139	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	117	2014
Autonomous cross-domain knowledge transfer in lifelong policy gradient reinforcement learning HB Ammar, E Eaton, JM Luna, P Ruvolo International Joint Conference on Artificial Intelligence, 3345-3351, 2015	109	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	104	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	104	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	88	2015
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	83	2022
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	81	2019
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	81	2012
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	65	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	63	2014
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	62*	2023
Balancing two-player stochastic games with soft q-learning J Grau-Moya, F Leibfried, H Bou-Ammar arXiv preprint arXiv:1802.03216, 2018	59	2018
Robot reinforcement learning on the constraint manifold P Liu, D Tateo, HB Ammar, J Peters Conference on Robot Learning, 1357-1366, 2022	56	2022
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	53	2010
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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