52 citations · 112 across the 24 of their papers we have counts for
6 papers · 1 filter
Few-for-Many Personalized Federated Learning
Ping Guo, Tiantian Zhang, Xi Lin +3
Personalized Federated Learning (PFL) aims to train customized models for clients with highly heterogeneous data distributions while preserving data privacy. Existing approaches of…
Learning to Reduce Search Space for Generalizable Neural Routing Solver
Changliang Zhou, Xi Lin, Zhenkun Wang +1
Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to construct approximate optimal s…
CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
Ping Guo, Qingfu Zhang, Xi Lin
The discovery of symbolic solutions -- mathematical expressions, logical rules, and algorithmic structures -- is fundamental to advancing scientific and engineering progress. Howev…
LLM4AD: A Platform for Algorithm Design with Large Language Model
Fei Liu, Rui Zhang, Zhuoliang Xie +10
We introduce LLM4AD, a unified Python platform for algorithm design (AD) with large language models (LLMs). LLM4AD is a generic framework with modularized blocks for search methods…
Multi-objective Evolution of Heuristic Using Large Language Model
Shunyu Yao, Fei Liu, Xi Lin +3
Heuristics are commonly used to tackle various search and optimization problems. Design heuristics usually require tedious manual crafting with domain knowledge. Recent works have…
Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver
Changliang Zhou, Xi Lin, Zhenkun Wang +3
In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial. It presents unique challenges driven…