49 citations · 141 across the 12 of their papers we have counts for
13 papers
ShapeCond: Fast Shapelet-Guided Dataset Condensation for Time Series Classification
Sijia Peng, Yun Xiong, Xi Chen +5
Time series data supports many domains (e.g., finance and climate science), but its rapid growth strains storage and computation. Dataset condensation can alleviate this by synthes…
TripleWin: Fixed-Point Equilibrium Pricing for Data-Model Coupled Markets
Hongrun Ren, Yun Xiong, Lei You +3
The rise of the machine learning (ML) model economy has intertwined markets for training datasets and pre-trained models. However, most pricing approaches still separate data and m…
Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need
Sijia Peng, Yun Xiong, Yangyong Zhu +1
Time series forecasting requires balancing short-term and long-term dependencies for accurate predictions. Existing methods mainly focus on long-term dependency modeling, neglectin…
RDGSL: Dynamic Graph Representation Learning with Structure Learning
Siwei Zhang, Yun Xiong, Yao Zhang +4
Temporal Graph Networks (TGNs) have shown remarkable performance in learning representation for continuous-time dynamic graphs. However, real-world dynamic graphs typically contain…
TIGER: Temporal Interaction Graph Embedding with Restarts
Yao Zhang, Yun Xiong, Yongxiang Liao +4
Temporal interaction graphs (TIGs), consisting of sequences of timestamped interaction events, are prevalent in fields like e-commerce and social networks. To better learn dynamic…
ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu, Yun Xiong, Yao Zhang +4
Since group activities have become very common in daily life, there is an urgent demand for generating recommendations for a group of users, referred to as group recommendation tas…
CLARE: A Semi-supervised Community Detection Algorithm
Xixi Wu, Yun Xiong, Yao Zhang +5
Community detection refers to the task of discovering closely related subgraphs to understand the networks. However, traditional community detection algorithms fail to pinpoint a p…
RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation
Yao Zhang, Yun Xiong, Yiheng Sun +4
Risk scoring systems have been widely deployed in many applications, which assign risk scores to users according to their behavior sequences. Though many deep learning methods with…
Triangle Graph Interest Network for Click-through Rate Prediction
Wensen Jiang, Yizhu Jiao, Qingqin Wang +6
Click-through rate prediction is a critical task in online advertising. Currently, many existing methods attempt to extract user potential interests from historical click behavior…
Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning
Yizhu Jiao, Yun Xiong, Jiawei Zhang +3
Graph representation learning has attracted lots of attention recently. Existing graph neural networks fed with the complete graph data are not scalable due to limited computation…
ISTD-GCN: Iterative Spatial-Temporal Diffusion Graph Convolutional Network for Traffic Speed Forecasting
Yi Xie, Yun Xiong, Yangyong Zhu
Most of the existing algorithms for traffic speed forecasting split spatial features and temporal features to independent modules, and then associate information from both dimensio…
Collective Link Prediction Oriented Network Embedding with Hierarchical Graph Attention
Yizhu Jiao, Yun Xiong, Jiawei Zhang +1
To enjoy more social network services, users nowadays are usually involved in multiple online sites at the same time. Aligned social networks provide more information to alleviate…
Defining Data Science
Yangyong Zhu, Yun Xiong
Data science is gaining more and more and widespread attention, but no consensus viewpoint on what data science is has emerged. As a new science, its objects of study and scientifi…