Asma Atamna

According to our database, Asma Atamna authored at least 15 papers between 2014 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Cumulative Learning Rate Adaptation: Revisiting Path-Based Schedules for SGD and Adam.

Asma Atamna, Tom Maus, Fabian Kievelitz, Tobias Glasmachers

CoRR, August, 2025

Leveraging Genetic Algorithms for Efficient Demonstration Generation in Real-World Reinforcement Learning Environments.

Tom Maus, Asma Atamna, Tobias Glasmachers

CoRR, July, 2025

2024

Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering.

Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

2023

ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation.

Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna

Proceedings of the Machine Learning, Optimization, and Data Science, 2023

2022

Benchmarking several strategies to update the penalty parameters in AL-CMA-ES on the bbob-constrained testbed.

Paul Dufossé, Asma Atamna

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021

Convex optimization with an interpolation-based projection and its application to deep learning.

Riad Akrour, Asma Atamna, Jan Peters

Mach. Learn., 2021

2020

On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling.

Asma Atamna, Anne Auger, Nikolaus Hansen

Theor. Comput. Sci., 2020

HRI-RNN: A User-Robot Dynamics-Oriented RNN for Engagement Decrease Detection.

Asma Atamna, Chloé Clavel

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks.

Asma Atamna, Nataliya Sokolovska, Jean-Claude Crivello

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

2017

Analysis of Randomized Adaptive Algorithms for Black-Box Continuous Constrained Optimization. (Analyse d'algorithmes stochastiques adaptatifs pour l'optimisation numérique boîte-noire avec contraintes).

Asma Atamna

PhD thesis, 2017

Linearly Convergent Evolution Strategies via Augmented Lagrangian Constraint Handling.

Asma Atamna, Anne Auger, Nikolaus Hansen

Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2017

2016

Augmented Lagrangian Constraint Handling for CMA-ES - Case of a Single Linear Constraint.

Asma Atamna, Anne Auger, Nikolaus Hansen

Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Analysis of Linear Convergence of a (1 + 1)-ES with Augmented Lagrangian Constraint Handling.

Asma Atamna, Anne Auger, Nikolaus Hansen

Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

2015

Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed.

Asma Atamna

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2014

How to Assess Step-Size Adaptation Mechanisms in Randomised Search.

Nikolaus Hansen, Asma Atamna, Anne Auger

Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014