English(EN) Efficient Constant Optimization for Symbolic Regression with GPU-Accelerated Tree-Based Genetic Programming

GPU 加速求解器提升遗传编程的符号回归效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-03 04:20

研究人员开发了一种新颖的 GPU 常驻求解器，用于通过遗传编程优化符号回归中的常数。这种批处理的 Levenberg-Marquardt 求解器可有效处理表达式树的异构种群，在 NVIDIA A100 硬件上实现高吞吐量。与标准的遗传编程方法相比，该方法显著提高了恢复控制方程的能力。 AI

影响这种新方法通过提高遗传编程技术的效率，有可能加速科学定律和数学模型的发现。

排序理由详细介绍符号回归新计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Yuntian Chen · 2026-09-03 04:20

面向符号回归的高效常数优化，采用GPU加速的基于树的遗传编程

Constant optimization refines the numerical coefficients of candidate expressions in tree-based genetic programming for symbolic regression. But its per-generation cost has led modern GPU-accelerated frameworks to omit it or restrict it to lightweight forms. We present a GPU-resi…