Evolutionary Systems
Symbolic Regression with a Learned Concept Library
SR, uses zero-shot queries to a large language model (LLM) to discover and evolve abstract concepts occurring in known high-performing hypotheses.
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
Krzysztof M. Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Vikas Sindhwani
Neural Information Processing Systems http://nips.cc/
Max-value Entropy Search for Multi-Objective Bayesian Optimization
Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa
Neural Information Processing Systems http://nips.cc/
ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution Haoran Y e
The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design automation has gained new momentum with the rise of large language models (LLMs).
ANODEV2: A Coupled Neural ODE Framework
Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E. Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros
Neural Information Processing Systems http://nips.cc/
