Search Results - "Bou Ammar, Haitham"

Factored four way conditional restricted Boltzmann machines for activity recognition by Mocanu, Decebal Constantin, Bou Ammar, Haitham, Lowet, Dietwig, Driessens, Kurt, Liotta, Antonio, Weiss, Gerhard, Tuyls, Karl

“…•This paper proposes a new learning algorithm for human activity recognition.•Its name is factored four way conditional restricted Boltzmann machine…”
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Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines by Mocanu, Decebal Constantin, Bou Ammar, Haitham, Puig, Luis, Eaton, Eric, Liotta, Antonio

“…•Estimation of 3D trajectories from their 2D projections given by one camera source.•Disjunctive factored four way conditional restricted Boltzmann machine…”
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On the prevalence of hierarchies in social networks by Ranjbar-Sahraei, Bijan, Bou Ammar, Haitham, Tuyls, Karl, Weiss, Gerhard

“…In this paper, we introduce two novel evolutionary processes for hierarchical networks referred to as dominance- and prestige-based evolution models, i.e.,…”
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Distributed Newton Method for Large-Scale Consensus Optimization by Tutunov, Rasul, Bou-Ammar, Haitham, Jadbabaie, Ali

“…In this paper, we propose a distributed Newton method for decenteralized optimization of large sums of convex functions. Our proposed method is based on…”
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Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions by Du, Desong, Han, Shaohang, Qi, Naiming, Ammar, Haitham Bou, Wang, Jun, Pan, Wei

“…Reinforcement learning (RL) exhibits impressive performance when managing complicated control tasks for robots. However, its wide application to physical…”
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Scalable lifelong reinforcement learning by Zhan, Yusen, Ammar, Haitham Bou, Taylor, Matthew E.

“…•Deriving a novel scalable algorithm for lifelong policy search in reinforcement learning.•Acquiring linear convergence rate of our new algorithm•Demonstrating…”
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Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks by Kicki, Piotr, Liu, Puze, Tateo, Davide, Bou-Ammar, Haitham, Walas, Krzysztof, Skrzypczynski, Piotr, Peters, Jan

“…Motion planning is a mature area of research in robotics with many well-established methods based on optimization or sampling the state space, suitable for…”
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BOiLS: Bayesian Optimisation for Logic Synthesis by Grosnit, Antoine, Malherbe, Cedric, Tutunov, Rasul, Wan, Xingchen, Wang, Jun, Ammar, Haitham Bou

“…Optimising the quality-of-results (QoR) of circuits during logic synthesis is a formidable challenge necessitating the exploration of exponentially sized…”
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SAMBA: safe model-based & active reinforcement learning by Cowen-Rivers, Alexander I., Palenicek, Daniel, Moens, Vincent, Abdullah, Mohammed Amin, Sootla, Aivar, Wang, Jun, Bou-Ammar, Haitham

“…In this paper, we propose SAMBA, a novel framework for safe reinforcement learning that combines aspects from probabilistic modelling, information theory, and…”
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Efficient and Reactive Planning for High Speed Robot Air Hockey by Liu, Puze, Tateo, Davide, Bou-Ammar, Haitham, Peters, Jan

“…Highly dynamic robotic tasks require high-speed and reactive robots. These tasks are particularly challenging due to the physical constraints, hardware…”
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HEBO: An Empirical Study of Assumptions in Bayesian Optimisation by Cowen-Rivers, Alexander I., Lyu, Wenlong, Tutunov, Rasul, Wang, Zhi, Grosnit, Antoine, Griffiths, Ryan Rhys, Maraval, Alexandre Max, Jianye, Hao, Wang, Jun, Peters, Jan, Bou-Ammar, Haitham

“…In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate…”
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Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines by Mocanu, Decebal Constantin, Ammar, Haitham Bou, Puig, Luis, Eaton, Eric, Liotta, Antonio

“…Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an…”
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HEBO: Pushing The Limits of Sample-Efficient Hyper-parameter Optimisation by Cowen-Rivers, Alexander I, Lyu, Wenlong, Tutunov, Rasul, Wang, Zhi, Grosnit, Antoine, Griffiths, Ryan Rhys, Maraval, Alexandre Max, Hao Jianye, Wang, Jun, Peters, Jan, Bou-Ammar, Haitham

“…In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate…”
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Lightweight Structural Choices Operator for Technology Mapping by Grosnit, Antoine, Zimmer, Matthieu, Tutunov, Rasul, Li, Xing, Chen, Lei, Yang, Fan, Yuan, Mingxuan, Bou-Ammar, Haitham

“…Technology mapping quality heavily depends on the subject graph structure. To overcome structural biases, operators construct choice nodes to enable mappings…”
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Toward real-world automated antibody design with combinatorial Bayesian optimization by Khan, Asif, Cowen-Rivers, Alexander I., Grosnit, Antoine, Deik, Derrick-Goh-Xin, Robert, Philippe A., Greiff, Victor, Smorodina, Eva, Rawat, Puneet, Akbar, Rahmad, Dreczkowski, Kamil, Tutunov, Rasul, Bou-Ammar, Dany, Wang, Jun, Storkey, Amos, Bou-Ammar, Haitham

“…Antibodies are multimeric proteins capable of highly specific molecular recognition. The complementarity determining region 3 of the antibody variable heavy…”
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Inexpensive user tracking using Boltzmann Machines by Mocanu, Elena, Mocanu, Decebal Constantin, Ammar, Haitham Bou, Zivkovic, Zoran, Liotta, Antonio, Smirnov, Evgueni

“…Inexpensive user tracking is an important problem in various application domains such as healthcare, human-computer interaction, energy savings, safety,…”
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Are Random Decompositions all we need in High Dimensional Bayesian Optimisation? by Ziomek, Juliusz, Bou-Ammar, Haitham

“…Learning decompositions of expensive-to-evaluate black-box functions promises to scale Bayesian optimisation (BO) to high-dimensional problems. However, the…”
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Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization by Dreczkowski, Kamil, Grosnit, Antoine, Ammar, Haitham Bou

“…This paper introduces a modular framework for Mixed-variable and Combinatorial Bayesian Optimization (MCBO) to address the lack of systematic benchmarking and…”
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Contextual Causal Bayesian Optimisation by Arsenyan, Vahan, Grosnit, Antoine, Bou-Ammar, Haitham

“…Causal Bayesian optimisation (CaBO) combines causality with Bayesian optimisation (BO) and shows that there are situations where the optimal reward is not…”
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Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications by Liu, Puze, Bou-Ammar, Haitham, Peters, Jan, Tateo, Davide

“…Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments…”
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