Cover Image

Optimal Pattern Detection Tree for Symbolic Rule-Based Classification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hong, Young-Chae, Chen, Yangho
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting
by: Hong, Young-Chae, et al.
Published: (2025)

Double-Bounded Optimal Transport for Advanced Clustering and Classification
by: Shi, Liangliang, et al.
Published: (2024)

RECTOR: Priority-Aware Rule-Based Reranking for Compliance-Aware Autonomous Driving Trajectory Selection
by: Hajieghrary, Hadi, et al.
Published: (2026)

A Safe Screening Rule with Bi-level Optimization of $ν$ Support Vector Machine
by: Yang, Zhiji, et al.
Published: (2024)

Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning
by: Dickens, Charles, et al.
Published: (2024)

Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
by: Shafiee, Soroosh, et al.
Published: (2023)

Optimal Multimarginal Schrödinger Bridge: Minimum Spanning Tree over Measure-valued Vertices
by: Bondar, Georgiy A., et al.
Published: (2025)

Optimal Transport for Probabilistic Circuits
by: Ciotinga, Adrian, et al.
Published: (2024)

Optimal Transport for Machine Learners
by: Peyré, Gabriel
Published: (2025)

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control
by: Skifstad, Julian, et al.
Published: (2026)

Optimal and Diffusion Transports in Machine Learning
by: Peyré, Gabriel
Published: (2025)

DiscoverDCP: A Data-Driven Approach for Construction of Disciplined Convex Programs via Symbolic Regression
by: Myhre, Sveinung
Published: (2025)

Seeing Through Risk: A Symbolic Approximation of Prospect Theory
by: Yousaf, Ali Arslan, et al.
Published: (2025)

Optimal Control Operator Perspective and a Neural Adaptive Spectral Method
by: Feng, Mingquan, et al.
Published: (2024)

Benchmarking Reinforcement Learning via Stochastic Converse Optimality: Generating Systems with Known Optimal Policies
by: Ibrahim, Sinan, et al.
Published: (2026)

Performative Policy Gradient: Optimality in Performative Reinforcement Learning
by: Basu, Debabrota, et al.
Published: (2025)

SPOT: Spatio-Temporal Pattern Mining and Optimization for Load Consolidation in Freight Transportation Networks
by: Cheng, Sikai, et al.
Published: (2025)

On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
by: Ma, Shaocong, et al.
Published: (2025)

Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
by: Kan, Kelvin, et al.
Published: (2025)

Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem
by: Goh, Yong Liang, et al.
Published: (2022)

OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack
by: Gai, Kuo, et al.
Published: (2024)

Optimal Labeler Assignment and Sampling for Active Learning in the Presence of Imperfect Labels
by: Ahadi, Pouya, et al.
Published: (2025)

Optimal Power Grid Operations with Foundation Models
by: Puech, Alban, et al.
Published: (2024)

Isotropic Curvature Model for Understanding Deep Learning Optimization: Is Gradient Orthogonalization Optimal?
by: Su, Weijie
Published: (2025)

What Is the Alignment Tax?
by: Young, Robin
Published: (2026)

Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
by: Ding, Jianglin, et al.
Published: (2025)

PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
by: Klamkin, Michael, et al.
Published: (2025)

Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control
by: Kamboj, Ankur, et al.
Published: (2026)

Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
by: Rosemberg, Andrew, et al.
Published: (2025)

A Median Perspective on Unlabeled Data for Out-of-Distribution Detection
by: Abbas, Momin, et al.
Published: (2025)

Memory-Efficient LLM Pretraining via Minimalist Optimizer Design
by: Glentis, Athanasios, et al.
Published: (2025)

Dynamic Memory Based Adaptive Optimization
by: Szegedy, Balázs, et al.
Published: (2024)

gridfm-datakit-v1: A Python Library for Scalable and Realistic Power Flow and Optimal Power Flow Data Generation
by: Puech, Alban, et al.
Published: (2025)

Improving the Validity of Decision Trees as Explanations
by: Nemecek, Jiri, et al.
Published: (2023)

Centrality-Based Pruning for Efficient Echo State Networks
by: Laudari, Sudip
Published: (2026)

Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning
by: Adde, Nihal Acharya, et al.
Published: (2024)

Tree-Preconditioned Differentiable Optimization and Axioms as Layers
by: Liao, Yuexin
Published: (2025)

Reward-Directed Score-Based Diffusion Models via q-Learning
by: Gao, Xuefeng, et al.
Published: (2024)

Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent
by: Yang, Tong, et al.
Published: (2025)

From Optimization to Prediction: Transformer-Based Path-Flow Estimation to the Traffic Assignment Problem
by: Ameli, Mostafa, et al.
Published: (2025)