12 citations · 23 across the 19 of their papers we have counts for
9 papers · 1 filter
The Role of Social Support and Influencers in Social Media Communities
Junwei Su, Peter Marbach
How can individual agents coordinate their actions to achieve a shared objective in distributed systems? This challenge spans economic, technical, and sociological domains, each co…
Heta: Distributed Training of Heterogeneous Graph Neural Networks
Yuchen Zhong, Junwei Su, Chuan Wu +1
Heterogeneous Graph Neural Networks (HGNNs) leverage diverse semantic relationships in Heterogeneous Graphs (HetGs) and have demonstrated remarkable learning performance in various…
Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems
Junwei Su, Difan Zou, Chuan Wu
Stochastic gradient descent (SGD) exhibits strong algorithmic regularization effects in practice and plays an important role in the generalization of modern machine learning. Howev…
BG-HGNN: Toward Efficient Learning for Complex Heterogeneous Graphs
Junwei Su, Lingjun Mao, Zheng Da +1
Heterogeneous graphs, comprising diverse node and edge types connected through varied relations, are ubiquitous in real-world applications. Message-passing heterogeneous graph neur…
On the Topology Awareness and Generalization Performance of Graph Neural Networks
Junwei Su, Chuan Wu
Many computer vision and machine learning problems are modelled as learning tasks on graphs where graph neural networks GNNs have emerged as a dominant tool for learning representa…
PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
Junwei Su, Difan Zou, Chuan Wu
Memory-based Dynamic Graph Neural Networks (MDGNNs) are a family of dynamic graph neural networks that leverage a memory module to extract, distill, and memorize long-term temporal…
Towards Robust Graph Incremental Learning on Evolving Graphs
Junwei Su, Difan Zou, Zijun Zhang +1
Incremental learning is a machine learning approach that involves training a model on a sequence of tasks, rather than all tasks at once. This ability to learn incrementally from a…
MTRGL:Effective Temporal Correlation Discerning through Multi-modal Temporal Relational Graph Learning
Junwei Su, Shan Wu, Jinhui Li
In this study, we explore the synergy of deep learning and financial market applications, focusing on pair trading. This market-neutral strategy is integral to quantitative finance…
MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline
Guangming Sheng, Junwei Su, Chao Huang +1
Memory-based Temporal Graph Neural Networks (MTGNNs) are a class of temporal graph neural networks that utilize a node memory module to capture and retain long-term temporal depend…