Asma Atamna - RankMe

19 papers A 5B 1Journal 8Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Balancing Specialization and Centralization: A Multi-Agent Reinforcement Learning Benchmark for Sequential Industrial Control. CoRR Tom Maus, Asma Atamna, Tobias Glasmachers
2025	J	`jnl`	Cumulative Learning Rate Adaptation: Revisiting Path-Based Schedules for SGD and Adam. CoRR Asma Atamna, Tom Maus, Fabian Kievelitz, Tobias Glasmachers
2025	J	`jnl`	Leveraging Genetic Algorithms for Efficient Demonstration Generation in Real-World Reinforcement Learning Environments. CoRR Tom Maus, Asma Atamna, Tobias Glasmachers
2024	—	`conf`	Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering. ECML/PKDD (10) Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers
2024	J	`jnl`	Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering. CoRR Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers
2023	—	`conf`	ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation. LOD (1) Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna
2023	J	`jnl`	ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation. CoRR Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna
2022	—	`conf`	Benchmarking several strategies to update the penalty parameters in AL-CMA-ES on the bbob-constrained testbed. GECCO Companion Paul Dufossé, Asma Atamna
2021	J	`jnl`	Convex optimization with an interpolation-based projection and its application to deep learning. Mach. Learn. Riad Akrour, Asma Atamna, Jan Peters
2020	B	`conf`	A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks. IDA Asma Atamna, Nataliya Sokolovska, Jean-Claude Crivello
2020	J	`jnl`	Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning. CoRR Riad Akrour, Asma Atamna, Jan Peters
2020	A	`conf`	HRI-RNN: A User-Robot Dynamics-Oriented RNN for Engagement Decrease Detection. INTERSPEECH Asma Atamna, Chloé Clavel
2020	J	`jnl`	On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling. Theor. Comput. Sci. Asma Atamna, Anne Auger, Nikolaus Hansen
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
2017	A	`conf`	Linearly Convergent Evolution Strategies via Augmented Lagrangian Constraint Handling. FOGA Asma Atamna, Anne Auger, Nikolaus Hansen
2016	A	`conf`	Analysis of Linear Convergence of a (1 + 1)-ES with Augmented Lagrangian Constraint Handling. GECCO Asma Atamna, Anne Auger, Nikolaus Hansen
2016	A	`conf`	Augmented Lagrangian Constraint Handling for CMA-ES - Case of a Single Linear Constraint. PPSN Asma Atamna, Anne Auger, Nikolaus Hansen
2015	—	`conf`	Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed. GECCO (Companion) Asma Atamna
2014	A	`conf`	How to Assess Step-Size Adaptation Mechanisms in Randomised Search. PPSN Nikolaus Hansen, Asma Atamna, Anne Auger