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53 papers · 1 filter
DAS-PMVC: A Framework for Partial Multi-View Clustering via Dual Alignment and Structure Enhancement
Shubin Ma, Liang Zhao, Chuanye He +4
In recent years, multi-view clustering has attracted widespread research interest. However, due to limitations in data collection devices, data across different views often suffer…
PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting
Enqiang Zhu, Zhenbin Deng, Shengzhi Wang +2
In real-world applications, multimodal time-series forecasting faces a key challenge: textual information is often useful but unreliable. Auxiliary texts may contain irrelevant, am…
Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in Conversation
Xinran Li, Xiujuan Xu, Jiaqi Qiao
Emotion Recognition in Conversation (ERC) is a practical and challenging task. This paper proposes a novel multimodal approach, the Long-Short Distance Graph Neural Network (LSDGNN…
Towards Collaborative Fairness in Federated Learning Under Imbalanced Covariate Shift
Tianrun Yu, Jiaqi Wang, Haoyu Wang +4
Collaborative fairness is a crucial challenge in federated learning. However, existing approaches often overlook a practical yet complex form of heterogeneity: imbalanced covariate…
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection
Jing Ren, Mingliang Hou, Zhixuan Liu +1
Graph anomaly detection is a popular and vital task in various real-world scenarios, which has been studied for several decades. Recently, many studies extending deep learning-base…
Learnable cut flow for high energy physics
Jing Li, Hao Sun
Neural networks have emerged as a powerful paradigm for tasks in high energy physics, yet their opaque training process renders them as a black box. In contrast, the traditional cu…