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Machine Learning & Artificial Intelligence
Title: Distributed Multitask Reinforcement Learning with Quadratic Convergence
Venue: NeurIps, 2018
Authors: Rasul Tutunov, Dongho Kim, and Haitham Bou Ammar
Title: An Information-Theoretic Optimality Principle for Deep Reinforcement Learning
Venue: Reinforcement Learning Workshop, NeurIps 2018
Authors: Felix Leibfried, Jordi Grau-Moya, Haitham Bou Ammar
Title: Model-Based Stabilisation of Deep Reinforcement Learning
Venue: arXiv e-Prints, 2018
Authors: Felix Leibfried, Rasul Tutunov, Peter Vrancx, Haitham Bou Ammar
Title: Learning High-Level Representation from Demonstrations
Venue: arXiv e-Prints, 2018
Authors: Garrett Anderson, Peter Vrancx, Haitham Bou Ammar
Title: Balancing Two-Player Stochastic Games with Soft Q-Learning
Venue: IJCAI, 2018
Authors: Jordi Grau-Moya, Felix Leibfried, Haitham Bou Ammar
Title: Scalable Lifelong Reinforcement Learning
Venue: Patter Recognition Journal, 2017
Authors: Yusen Zhan, Haitham Bou Ammar, Matthew E. Taylor
Title: Scalable Lifelong Reinforcement Learning
Venue: Patter Recognition Journal, 2017
Authors: Yusen Zhan, Haitham Bou Ammar, Matthew E. Taylor
Venue: Conference on Decision and Control (CDC), 2017
Authors: Julia El-Zini, Rasul Tutunov, Haitham Bou Ammar, Ali Jadbabie
Title: Non-Convex Policy Search Using Variational Inequalities
Venue: Journal on Neural Computation, 2017
Authors: Yusen Zhan, Haitham Bou Ammar, Matthew E. Taylor
Title: Scalable Multitask Policy Gradients Reinforcement Learning
Venue: AAAI, 2017
Authors: Salam El-Bsat, Haitham Bou Ammar, Matthew E. Taylor
Title: Estimating 3d trajectories from 2d projections via four-way conditional restricted boltzmann machines
Venue: Journal on Pattern Recognition, 2017
Authors: Salam El-Bsat, Haitham Bou Ammar, Matthew E. Taylor
Title: An Exact Distributed Newton Method for Reinforcement Learning
Venue: Conference on Decision and Control, 2016
Authors: Rasul Tutunov, Haitham Bou Ammar, Ali Jadbabaie
Title: Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning
Venue: IJCAI, 2016
Authors: Yusen Zhan, Haitham Bou Ammar, Matthew E. Taylor
Title: Autonomous Cross-Domain Transfer in Lifelong Reinforcement Learning
Venue: IJCAI, 2015 (Best paper award nomination)
Authors: Haitham Bou Ammar, Eric Eaton, Jose Marcio Luna, Paul Ruvolo
Title: Safe Policy Search for Lifelong Reinforcement Learning with Sub-Linear Regret
Venue: ICML, 2015
Authors: Haitham Bou Ammar, Rasul Tutunov, Eric Eaton
Title: Online Multi-Task Learning for Policy Gradient Methods
Venue: ICML, 2014
Authors: Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
Title: An Automated Measure for MDP Similarity for Transfer Learning
Venue: AAAI, 2014 (Workshop)
Authors: Haitham Bou Ammar, Eric Eaton, Decebal Mocanu, Kurt Driessens, Gerhard Weiss, Kar Tuyls
Title: Online Multi-Task Gradient Temporal Difference Learning
Venue: AAAI, 2014
Authors: Vishnu Sreenivasan, Haitham Bou Ammar, Eric Eaton
Title: Inexpensive User Tracking Using Boltzmann Machines
Venue: Conference on Systems Man and Cybernetics, 2014
Authors: Elena Mocanu, Decebal Mocanu, Haitham Bou Ammar, A. Liota, and E. Smirnov
Title: Factored Four-Way Conditional Restricted Boltzmann Machines
Venue: Journal on Pattern Recognition, 2014
Authors: Decebal Mocanu, Haitham Bou Ammar, A. Liota, Kurt Driessens, Karl Tuyls, Gerhard Weiss
Title: Automatically Mapped Transfer Between Reinforcement Learning Tasks
Venue: ECML, 2013
Authors: Haitham Bou Ammar, Decebal Mocanu, Kurt Driessens, Karl Tuyls
Title: Automated Transfer for Reinforcement Learning
Venue: German Journal on Artificial Intelligence, 2013
Authors: Haitham Bou Ammar, Karl Tuyls, Gerhard Weiss
Title: Automated Negotiation using Sparse Gaussian Processes
Venue: AAMAS, 2013
Authors: Siqi Chen, Haitham Bou Ammar, Karl Tuyls, Gerhard Weiss
Title: Conditional Restricted Boltzmann Machines for Automated Negotiations
Venue: IJCAI, 2013
Authors: Siqi Chen, Haitham Bou Ammar, Karl Tuyls, Gerhard Weiss
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