Haitham Bou-Ammar

Gerhard Weiss, Haitham Bou-Ammar, Bijan Ranjbar Sahraei, 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

On the Degree Distribution of Pólya Urn Graph Processes pdf

Eric Eaton, Haitham Bou-Ammar, Ali Jadbabaie, 2014, ArXiv.

Efficient and Reactive Planning for High Speed Robot Air Hockey

Haitham Bou-Ammar, Jan Peters, Davide Tateo, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning pdf

Zhitang Chen, Haitham Bou-Ammar, Jan Peters, 2021, ArXiv.

Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? pdf

Haitham Bou-Ammar, Ryan-Rhys Griffiths, Jun Wang, 2020, J. Mach. Learn. Res..

HEBO: Heteroscedastic Evolutionary Bayesian Optimisation pdf

Haitham Bou-Ammar, Jianye Hao, Zhi Wang, 2020, ArXiv.

Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment

Eric Eaton, Haitham Bou-Ammar, Matthew E. Taylor, 2015, AAAI.

Toward real-world automated antibody design with combinatorial Bayesian optimization

R. Akbar, Philippe A. Robert, V. Greiff, 2023, Cell reports methods.

Evolution of cooperation in arbitrary complex networks

Gerhard Weiss, Haitham Bou-Ammar, Bijan Ranjbar Sahraei, 2014, AAMAS.

Online Double Oracle

Le Cong Dinh, Nicolas Perez Nieves, Yaodong Yang, 2021, Trans. Mach. Learn. Res..

Wasserstein Robust Reinforcement Learning pdf

Haitham Bou-Ammar, Mohammed Abdullah, Jun Wang, 2019, ArXiv.

Reinforcement Learning in Presence of Discrete Markovian Context Evolution

Jun Wang, Haitham Bou-Ammar, Taher Jafferjee, 2022, ICLR.

Multi-View Reinforcement Learning

Haitham Bou-Ammar, Lisheng Wu, Jun Wang, 2019, NeurIPS.

Robot Reinforcement Learning on the Constraint Manifold

Haitham Bou-Ammar, Jan Peters, Davide Tateo, 2021, CoRL.

Theory of Cooperation in Complex Social Networks

Gerhard Weiss, Haitham Bou-Ammar, Bijan Ranjbar Sahraei, 2014, AAAI.

Inexpensive user tracking using Boltzmann Machines

Haitham Bou-Ammar, Decebal Constantin Mocanu, Antonio Liotta, 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Distributed Newton Method for Large-Scale Consensus Optimization

Haitham Bou-Ammar, Ali Jadbabaie, Rasul Tutunov, 2016, IEEE Transactions on Automatic Control.

Scalable lifelong reinforcement learning

Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor, 2017, Pattern Recognit..

Online Multi-Task Learning for Policy Gradient Methods

Eric Eaton, Haitham Bou-Ammar, Matthew E. Taylor, 2014, ICML.

Compositional ADAM: An Adaptive Compositional Solver

Jun Wang, Rasul Tutunov, Haitham Bou-Ammar, 2020, ArXiv.

Enhancing Safe Exploration Using Safety State Augmentation

Haitham Bou-Ammar, Jun Wang, A. Cowen-Rivers, 2022, NeurIPS.

Optimizing complex automated negotiation using sparse pseudo-input gaussian processes

Gerhard Weiss, Haitham Bou-Ammar, Karl Tuyls, 2013, AAMAS.

Factored four way conditional restricted Boltzmann machines for activity recognition

Haitham Bou-Ammar, Kurt Driessens, Karl Tuyls, 2015, Pattern Recognit. Lett..

Reinforcement learning transfer via sparse coding

Haitham Bou-Ammar, Matthew E. Taylor, Kurt Driessens, 2012, AAMAS.

On the prevalence of hierarchies in social networks

K. Tuyls, Haitham Bou-Ammar, Gerhard Weiss, 2016, Social Network Analysis and Mining.

A Fast Distributed Solver for Symmetric Diagonally Dominant Linear Equations pdf

Haitham Bou-Ammar, Ali Jadbabaie, Rasul Tutunov, 2015, ArXiv.

αα-Rank: Practically Scaling α-Rank through Stochastic Optimisation

Haitham Bou-Ammar, Yaodong Yang, Rasul Tutunov, 2020, AAMAS.

Implicit Variational Conditional Sampling with Normalizing Flows pdf

Haitham Bou-Ammar, Aivar Sootla, Vincent Moens, 2021, ArXiv.

Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions

Haitham Bou-Ammar, Jun Wang, Wei Pan, 2023, 2023 IEEE International Conference on Robotics and Automation (ICRA).

αα-Rank: Scalable Multi-agent Evaluation through Evolution pdf

Haitham Bou-Ammar, Yaodong Yang, Jun Wang, 2019, ArXiv.

Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning Settings with Applications to Negative Transfer pdf

Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor, 2016, IJCAI.

Transfer for Automated Negotiation

K. Tuyls, Haitham Bou-Ammar, Gerhard Weiss, 2014, KI - Künstliche Intelligenz.

Conditional Restricted Boltzmann Machines for Negotiations in Highly Competitive and Complex Domains

Gerhard Weiss, Haitham Bou-Ammar, Karl Tuyls, 2013, IJCAI.

Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization

Haitham Bou-Ammar, Antoine Grosnit, Kamil Dreczkowski, 2023, arXiv.org.

Learning High-level Representations from Demonstrations pdf

Haitham Bou-Ammar, Peter Vrancx, Garrett Andersen, 2018, ArXiv.

An Information-Theoretic Optimality Principle for Deep Reinforcement Learning pdf

Haitham Bou-Ammar, Jordi Grau-Moya, Felix Leibfried, 2017, ArXiv.

Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning

Eric Eaton, Haitham Bou-Ammar, Paul Ruvolo, 2015, IJCAI.

SAMBA: safe model-based & active reinforcement learning pdf

Jun Wang, Aivar Sootla, Alexander I. Cowen-Rivers, 2020, Machine Learning.

Influencing Social Networks: An Optimal Control Study

Gerhard Weiss, Haitham Bou-Ammar, Bijan Ranjbar Sahraei, 2014, ECAI.

Learning to Communicate Implicitly by Actions pdf

Lisheng Wu, Zheng Tian, Jun Wang, 2018, AAAI.

An exact distributed newton method for reinforcement learning

Haitham Bou-Ammar, Ali Jadbabaie, Rasul Tutunov, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping

Gerhard Weiss, Haitham Bou-Ammar, Matthew E. Taylor, 2011, EUMAS.

Distributed lifelong reinforcement learning with sub-linear regret

Haitham Bou-Ammar, Ali Jadbabaie, Rasul Tutunov, 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

Evolutionary Dynamics of Ant Colony Optimization

Haitham Bou-Ammar, Karl Tuyls, Michael Kaisers, 2012, MATES.

Self-consistent Gradient-like Eigen Decomposition in Solving Schrödinger Equations

Rasul Tutunov, Haitham Bou-Ammar, Xiang Chen, 2022, ArXiv.

Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment

Matthew E. Taylor, Haitham Bou-Ammar, Eric Eaton, 2015, AAAI.

Reinforcement Learning Transfer via Common Subspaces

Haitham Bou-Ammar, Matthew E. Taylor, Haitham Bou-Ammar, 2011, ALA.

Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning

Haitham Bou-Ammar, Filippos Christianos, Georgios Papoudakis, 2023, ArXiv.

Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization

Haitham Bou-Ammar, Antoine Grosnit, Kamil Dreczkowski, 2023, NeurIPS.

αα-Rank: Practically Scaling α-Rank through Stochastic Optimisation

Yaodong Yang, H. Ammar, Rasul Tutunov, 2019, AAMAS.

Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks

Jan Peters, Haitham Bou-Ammar, Davide Tateo, 2023, IEEE Transactions on Robotics.

Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines

Matthew E. Taylor, K. Tuyls, K. Driessens, 2013, ECML/PKDD.

Contextual Causal Bayesian Optimisation

Haitham Bou-Ammar, Antoine Grosnit, Vahan Arsenyan, 2023, ArXiv.

Scalable lifelong reinforcement learning

Matthew E. Taylor, Haitham Bou-Ammar, Yusen Zhan, 2017, Pattern Recognit..

Distributed Multitask Reinforcement Learning with Quadratic Convergence

Haitham Bou-Ammar, Rasul Tutunov, Dongho Kim, 2018, NeurIPS.

ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning

Christopher E. Mower, Haitham Bou-Ammar, Yuzheng Zhuang, 2024, ArXiv.