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ORCIDAsma Atamna
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- affiliation: Ruhr-Universität Bochum, Germany
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2020 – today
- 2024
[c10]Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers:
Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering. ECML/PKDD (10) 2024: 150-165- [i3]Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers:
Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering. CoRR abs/2404.02577 (2024) - 2023
- [c9]Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna:
ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation. LOD (1) 2023: 78-92 - [i2]Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna:
ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation. CoRR abs/2307.02991 (2023) - 2022
- [c8]Paul Dufossé, Asma Atamna
:
Benchmarking several strategies to update the penalty parameters in AL-CMA-ES on the bbob-constrained testbed. GECCO Companion 2022: 1691-1699 - 2021
- [j2]Riad Akrour, Asma Atamna, Jan Peters:
Convex optimization with an interpolation-based projection and its application to deep learning. Mach. Learn. 110(8): 2267-2289 (2021) - 2020
- [j1]Asma Atamna, Anne Auger, Nikolaus Hansen:
On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling. Theor. Comput. Sci. 832: 68-97 (2020) - [c7]Asma Atamna, Nataliya Sokolovska, Jean-Claude Crivello:
A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks. IDA 2020: 27-39 - [c6]Asma Atamna, Chloé Clavel:
HRI-RNN: A User-Robot Dynamics-Oriented RNN for Engagement Decrease Detection. INTERSPEECH 2020: 4198-4202 - [i1]Riad Akrour, Asma Atamna, Jan Peters:
Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning. CoRR abs/2011.07016 (2020)
2010 – 2019
- 2017
- [b1]Asma Atamna:
Analysis of Randomized Adaptive Algorithms for Black-Box Continuous Constrained Optimization. (Analyse d'algorithmes stochastiques adaptatifs pour l'optimisation numérique boîte-noire avec contraintes). University of Paris-Saclay, France, 2017 - [c5]Asma Atamna, Anne Auger, Nikolaus Hansen:
Linearly Convergent Evolution Strategies via Augmented Lagrangian Constraint Handling. FOGA 2017: 149-161 - 2016
- [c4]Asma Atamna, Anne Auger, Nikolaus Hansen:
Analysis of Linear Convergence of a (1 + 1)-ES with Augmented Lagrangian Constraint Handling. GECCO 2016: 213-220 - [c3]Asma Atamna, Anne Auger, Nikolaus Hansen:
Augmented Lagrangian Constraint Handling for CMA-ES - Case of a Single Linear Constraint. PPSN 2016: 181-191 - 2015
- [c2]Asma Atamna:
Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed. GECCO (Companion) 2015: 1135-1142 - 2014
- [c1]Nikolaus Hansen, Asma Atamna, Anne Auger:
How to Assess Step-Size Adaptation Mechanisms in Randomised Search. PPSN 2014: 60-69
Coauthor Index
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