16 citations · 17 across the 3 of their papers we have counts for
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cs.LG2026
AdaEva: Accelerating LLM-Driven Algorithm Design with Adaptive Partial Evaluation
Tai Nguyen, Fei Liu, Phong Le +2
Large Language Models (LLMs) are increasingly used for automated algorithm design. However the computational cost of evaluating the generated algorithms can be excessive. We consid…
cs.LG2026
Discovering Interpretable Multi-Parameter Control Policies for Evolutionary Algorithms Using Deep Reinforcement Learning
Tai Nguyen, Phong Le, Carola Doerr +1
While deep Reinforcement Learning (deep-RL) has been increasingly applied to parameter control in evolutionary algorithms, rigorous theoretical analysis of parameter control remain…
cs.LG2023★ 1 cited
Using Automated Algorithm Configuration for Parameter Control
Deyao Chen, Maxim Buzdalov, Carola Doerr +1
Dynamic Algorithm Configuration (DAC) tackles the question of how to automatically learn policies to control parameters of algorithms in a data-driven fashion. This question has re…