16 citations · 17 across the 3 of their papers we have counts for
4 papers
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…
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…
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…
Hyper-Parameter Tuning for the (1+(λ,λ)) GA
Nguyen Dang, Carola Doerr
It is known that the ~Genetic Algorithm (GA) with self-adjusting parameter choices achieves a linear expected optimization time on OneMax if its hyper-parameters are sui…