Cover Image

On the Generalization Bounds of Symbolic Regression with Genetic Programming

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nomura, Masahiro, Hamano, Ryoki, Ono, Isao
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Diversified Residual Symbolic Regression
by: Ikeda, Koki, et al.
Published: (2026)

Natural Gradient Interpretation of Rank-One Update in CMA-ES
by: Hamano, Ryoki, et al.
Published: (2024)

A Memetic Algorithm based on Variational Autoencoder for Black-Box Discrete Optimization with Epistasis among Parameters
by: Kato, Aoi, et al.
Published: (2025)

cmaes: A Simple yet Practical Python Library for CMA-ES
by: Nomura, Masahiro, et al.
Published: (2024)

Adaptive Stochastic Natural Gradient Method for Safe Optimization on Binary Space
by: Uchida, Kento, et al.
Published: (2026)

CMA-ES for Safe Optimization
by: Uchida, Kento, et al.
Published: (2024)

CatCMA : Stochastic Optimization for Mixed-Category Problems
by: Hamano, Ryoki, et al.
Published: (2024)

CatCMA with Margin for Single- and Multi-Objective Mixed-Variable Black-Box Optimization
by: Hamano, Ryoki, et al.
Published: (2025)

Marginal Probability-Based Integer Handling for CMA-ES Tackling Single-and Multi-Objective Mixed-Integer Black-Box Optimization
by: Hamano, Ryoki, et al.
Published: (2022)

Tail Bounds on the Runtime of Categorical Compact Genetic Algorithm
by: Hamano, Ryoki, et al.
Published: (2024)

Transformer Semantic Genetic Programming for d-dimensional Symbolic Regression Problems
by: Anthes, Philipp, et al.
Published: (2025)

Multi-start Optimization Method via Scalarization based on Target Point-based Tchebycheff Distance for Multi-objective Optimization
by: Nagakane, Kota, et al.
Published: (2025)

Guiding Multi-Objective Genetic Programming with Description Length Improves Symbolic Regression Solutions
by: Kronberger, Gabriel, et al.
Published: (2026)

CMA-ES for Discrete and Mixed-Variable Optimization on Sets of Points
by: Uchida, Kento, et al.
Published: (2024)

CMA-ES with Learning Rate Adaptation
by: Nomura, Masahiro, et al.
Published: (2024)

Discovering Continuous-Time Memory-Based Symbolic Policies using Genetic Programming
by: de Vries, Sigur, et al.
Published: (2024)

Transformer Semantic Genetic Programming for Symbolic Regression
by: Anthes, Philipp, et al.
Published: (2025)

Neuro-Evolutionary Approach to Physics-Aware Symbolic Regression
by: Kubalík, Jiří, et al.
Published: (2025)

Enhancing Generalization in Evolutionary Feature Construction for Symbolic Regression through Vicinal Jensen Gap Minimization
by: Zhang, Hengzhe, et al.
Published: (2026)

Interpretable Non-linear Survival Analysis with Evolutionary Symbolic Regression
by: Rovito, Luigi, et al.
Published: (2025)

Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing
by: Aldeia, Guilherme Seidyo Imai, et al.
Published: (2024)

Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models
by: Haut, Nathan, et al.
Published: (2025)

GPU-Accelerated Genetic Programming for Symbolic Regression with Beagle Framework
by: Haut, Nathan, et al.
Published: (2026)

Sharpness-Aware Minimization in Genetic Programming
by: Bakurov, Illya, et al.
Published: (2024)

Genetic Programming for Explainable Manifold Learning
by: Cravens, Ben, et al.
Published: (2024)

Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles
by: Hoekstra, Cas Oude, et al.
Published: (2025)

Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
by: Chen, Jiacheng, et al.
Published: (2024)

Learning Semantics-aware Search Operators for Genetic Programming
by: Wyrwiński, Piotr, et al.
Published: (2025)

Genetic Programming with Transformer-Based Mutation for Approximate Circuit Design
by: Galeta, Ondrej, et al.
Published: (2026)

CGP++ : A Modern C++ Implementation of Cartesian Genetic Programming
by: Kalkreuth, Roman, et al.
Published: (2024)

Active Learning in Symbolic Regression with Physical Constraints
by: Medina, Jorge, et al.
Published: (2023)

Symbolic Regression with Multimodal Large Language Models and Kolmogorov Arnold Networks
by: Harvey, Thomas R., et al.
Published: (2025)

Self-Supervised Neural Architecture Search for Multimodal Deep Neural Networks
by: Suzuki, Shota, et al.
Published: (2025)

EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming
by: Yang, Xuanhao, et al.
Published: (2026)

Curriculum Learning in Genetic Programming Guided Local Search for Large-scale Vehicle Routing Problems
by: Liu, Saining, et al.
Published: (2025)

Data-Driven Discovery of Interpretable Kalman Filter Variants through Large Language Models and Genetic Programming
by: Saketos, Vasileios, et al.
Published: (2025)

Enhanced Genetic Programming Models with Multiple Equations for Accurate Semi-Autogenous Grinding Mill Throughput Prediction
by: Ghasemi, Zahra, et al.
Published: (2023)

Generalization Bounds and Model Complexity for Kolmogorov-Arnold Networks
by: Zhang, Xianyang, et al.
Published: (2024)

Symbolically Regressing Fish Biomass Spectral Data: A Linear Genetic Programming Method with Tunable Primitives
by: Huang, Zhixing, et al.
Published: (2025)

Neural-Symbolic Integration with Evolvable Policies
by: Thoma, Marios, et al.
Published: (2026)