3 papers
math.OC2026
Subsampled Ensemble Can Improve Generalization Tail Exponentially
Huajie Qian, Donghao Ying, Henry Lam +1
Ensemble learning is a popular technique to improve the accuracy of machine learning models. It traditionally hinges on the rationale that aggregating multiple weak models can lead…
cs.AI2025
SymAgent: A Neural-Symbolic Self-Learning Agent Framework for Complex Reasoning over Knowledge Graphs
Ben Liu, Jihai Zhang, Fangquan Lin +3
Recent advancements have highlighted that Large Language Models (LLMs) are prone to hallucinations when solving complex reasoning problems, leading to erroneous results. To tackle…
math.OC2024
Solving General Natural-Language-Description Optimization Problems with Large Language Models
Jihai Zhang, Wei Wang, Siyan Guo +4
Optimization problems seek to find the best solution to an objective under a set of constraints, and have been widely investigated in real-world applications. Modeling and solving…