33 citations · 66 across the 11 of their papers we have counts for
5 papers · 1 filter
CDR: Conservative Doubly Robust Learning for Debiased Recommendation
ZiJie Song, JiaWei Chen, Sheng Zhou +4
In recommendation systems (RS), user behavior data is observational rather than experimental, resulting in widespread bias in the data. Consequently, tackling bias has emerged as a…
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Zhiyao Zhou, Sheng Zhou, Bochao Mao +7
Graph Neural Networks (GNNs) have emerged as the de facto standard for representation learning on graphs, owing to their ability to effectively integrate graph topology and node at…
A Geometric Perspective on Diffusion Models
Defang Chen, Zhenyu Zhou, Jian-Ping Mei +3
Recent years have witnessed significant progress in developing effective training and fast sampling techniques for diffusion models. A remarkable advancement is the use of stochast…
Jointly Complementary&Competitive Influence Maximization with Concurrent Ally-Boosting and Rival-Preventing
Qihao Shi, Wenjie Tian, Wujian Yang +3
In this paper, we propose a new influence spread model, namely, Complementary\&Competitive Independent Cascade (CIC) model. CIC model generalizes three well known influence…
Robust Sequence Networked Submodular Maximization
Qihao Shi, Bingyang Fu, Can Wang +4
In this paper, we study the \underline{R}obust \underline{o}ptimization for \underline{se}quence \underline{Net}worked \underline{s}ubmodular maximization (RoseNets) problem. We in…