Publications (11)
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems
Shiqing Liu, Xueming Yan, Yaochu Jin
In recent years, there has been a notable surge in research on machine learning techniques for combinatorial optimization. It has been shown that learning-based methods outperform…
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Shangshang Yang, Xiaoshan Yu, Ye Tian +3
Knowledge tracing (KT) aims to trace students' knowledge states by predicting whether students answer correctly on exercises. Despite the excellent performance of existing Transfor…
A Graph Neural Network with Negative Message Passing for Graph Coloring
Xiangyu Wang, Xueming Yan, Yaochu Jin
Graph neural networks have received increased attention over the past years due to their promising ability to handle graph-structured data, which can be found in many real-world pr…
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks
Yaochu Jin, Xueming Yan, Shiqing Liu +1
Graph neural networks (GNNs) have emerged as a powerful tool for solving combinatorial optimization problems (COPs), exhibiting state-of-the-art performance in both graph-structure…
OmniMER: Auxiliary-Enhanced LLM Adaptation for Indonesian Multimodal Emotion Recognition
Xueming Yan, Boyan Xu, Yaochu Jin +7
Indonesian, spoken by over 200 million people, remains underserved in multimodal emotion recognition research despite its dominant presence on Southeast Asian social media platform…
LacaDM: A Latent Causal Diffusion Model for Multiobjective Reinforcement Learning
Xueming Yan, Bo Yin, Yaochu Jin
Multiobjective reinforcement learning (MORL) poses significant challenges due to the inherent conflicts between objectives and the difficulty of adapting to dynamic environments. T…