activity
20152025
most citedConsRec: Learning Consensus Behind Interactions for Group Recommendation

49 citations · 151 across the 15 of their papers we have counts for

collaborators

16 papers

cs.LG2025

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…

cs.LG2024

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…

cs.LG2023★ 1 cited

SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding

Xi Chen, Yongxiang Liao, Yun Xiong +4

Temporal Interaction Graphs (TIGs) are widely employed to model intricate real-world systems such as financial systems and social networks. To capture the dynamism and interdepende…

cs.LG2023★ 1 cited

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…

cs.IR2023★ 1 cited

Dual Intents Graph Modeling for User-centric Group Discovery

Xixi Wu, Yun Xiong, Yao Zhang +2

Online groups have become increasingly prevalent, providing users with space to share experiences and explore interests. Therefore, user-centric group discovery task, i.e., recomme…

cs.LG2023

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…

cs.IR2023★ 49 cited

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…

cs.SI2022★ 39 cited

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…

cs.LG2022

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…

cs.LG2022★ 1 cited

ReCo: A Dataset for Residential Community Layout Planning

Xi Chen, Yun Xiong, Siqi Wang +4

Layout planning is centrally important in the field of architecture and urban design. Among the various basic units carrying urban functions, residential community plays a vital pa…

cs.AI2022★ 18 cited

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…

cs.IR2021★ 7 cited

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3

In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendat…

cs.LG2020★ 24 cited

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…

cs.SI2020★ 8 cited

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…

cs.SI2019★ 1 cited

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…

cs.DB2015★ 1 cited

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…