Haitham Bou-Ammar

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Rasul TutunovMassachusetts Institute of TechnologyVerified email at mit.edu
Karl TuylsResearch Scientist, Google DeepMind and Professor of computer science, University of LiverpoolVerified email at google.com
Gerhard WeissProfessor of Computer Science and Artificial Intelligence, Maastricht UniversityVerified email at maastrichtuniversity.nl
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
Matthew E. TaylorAssociate Professor, University of AlbertaVerified email at ualberta.ca
Eric EatonUniversity of PennsylvaniaVerified email at cis.upenn.edu
Alexander I. Cowen-RiversDeepMindVerified email at deepmind.com
Decebal Constantin MocanuAssociate Professor in Machine Learning, University of Luxembourg, TU EindhovenVerified email at uni.lu
Antoine GrosnitResearch Scientist, Noah's Ark lab, LondonVerified email at huawei.com
Kurt DriessensAssociate Professor, Maastricht UniversityVerified email at maastrichtuniversity.nl
Siqi ChenTianjin UniversityVerified email at tju.edu.cn
Antonio LiottaProfessor at Faculty of Engineering, University of Bozen-Bolzano, ItalyVerified email at unibz.it
Felix LeibfriedEisler CapitalVerified email at eislercapital.com
Ali JadbabaieJR East Professor of Engineering, MITVerified email at mit.edu
Bijan Ranjbar-SahraeiFreelance Data ScientistVerified email at mydataexpert.nl
Jan PetersProfessor for Intelligent Autonomous Systems at Technische Universität DarmstadtVerified email at ias.tu-darmstadt.de
Holger VoosUniversity of Luxembourg, SnT Automation & Robotics Research GroupVerified email at uni.lu
Aivar Sootlaresearch associateVerified email at eng.ox.ac.uk
Yaodong YangAssistant Professor@Peking UniversityVerified email at pku.edu.cn
Daan BloembergenAI Researcher, City of AmsterdamVerified email at amsterdam.nl

Haitham Bou-Ammar

Reinforcement Learning Team Leader @ Huawei London & H. Assistant Professor @ UCL

Verified email at huawei.com

Machine Learning Reinforcement Learning Optimisation Variational Inference


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Online multi-task learning for policy gradient methods HB Ammar, E Eaton, P Ruvolo, M Taylor International conference on machine learning, 1206-1214, 2014	170	2014
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	119	2010
Smarts: Scalable multi-agent reinforcement learning training school for autonomous driving M Zhou, J Luo, J Villella, Y Yang, D Rusu, J Miao, W Zhang, M Alban, ... arXiv preprint arXiv:2010.09776, 2020	113	2020
An automated measure of mdp similarity for transfer in reinforcement learning HB Ammar, E Eaton, ME Taylor, DC Mocanu, K Driessens, G Weiss, ... Workshops at the twenty-eighth AAAI conference on artificial intelligence 1, 2014	95	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	83	2015
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	80	2015
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	76*	2022
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	71	2012
Safe policy search for lifelong reinforcement learning with sublinear regret HB Ammar, R Tutunov, E Eaton International Conference on Machine Learning, 2361-2369, 2015	64	2015
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	59	2019
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	57	2016
Wasserstein robust reinforcement learning MA Abdullah, H Ren, HB Ammar, V Milenkovic, R Luo, M Zhang, J Wang arXiv preprint arXiv:1907.13196, 2019	54	2019
Balancing two-player stochastic games with soft q-learning J Grau-Moya, F Leibfried, H Bou-Ammar arXiv preprint arXiv:1802.03216, 2018	52	2018
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	51	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	49	2015
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	49	2014
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	37	2021
Optimizing complex automated negotiation using sparse pseudo-input gaussian processes S Chen, HB Ammar, K Tuyls, G Weiss Proceedings of the 2013 international conference on Autonomous agents and …, 2013	34	2013
Reduced reference image quality assessment via boltzmann machines DC Mocanu, G Exarchakos, HB Ammar, A Liotta 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM …, 2015	33	2015
Automatically mapped transfer between reinforcement learning tasks via three-way restricted boltzmann machines HB Ammar, DC Mocanu, ME Taylor, K Driessens, K Tuyls, G Weiss Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013	33	2013

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