3 citations · 3 across the 5 of their papers we have counts for
5 papers
Robust Multi-view Clustering against Imperfect Information
Zhichao Huang, Haochen Zhou, Hao Wang +2
Real-world multi-view data always suffer from imperfect information problem, where the view-specific observations are absent (i.e., Incomplete Views, IV) and cross-view corresponde…
Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning
Jinjin Guo, Yexin Li, Zhichao Huang +5
Large-scale multimodal contrastive learning has recently achieved impressive success in learning rich and transferable representations, yet it remains fundamentally limited by the…
Graph Attention-based Adaptive Transfer Learning for Link Prediction
Huashen Lu, Wensheng Gan, Guoting Chen +2
Graph neural networks (GNNs) have brought revolutionary advancements to the field of link prediction (LP), providing powerful tools for mining potential relationships in graphs. Ho…
Core Knowledge Learning Framework for Graph Adaptation and Scalability Learning
Bowen Zhang, Zhichao Huang, Genan Dai +3
Graph classification is a pivotal challenge in machine learning, especially within the realm of graph-based data, given its importance in numerous real-world applications such as s…
EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection
Daijun Ding, Li Dong, Zhichao Huang +5
Stance detection aims to determine the attitude expressed in text towards a given target. Zero-shot stance detection (ZSSD) has emerged to classify stances towards unseen targets d…