232 citations · 1.4k across the 72 of their papers we have counts for
16 papers · 1 filter
EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph
Yuxiang Ren, Hao Zhu, Jiawei Zhang +2
Fraud detection is extremely critical for e-commerce business. It is the intent of the companies to detect and prevent fraud as early as possible. Existing fraud detection methods…
Scalable Heterogeneous Social Network Alignment through Synergistic Graph Partition
Yuxiang Ren, Lin Meng, Jiawei Zhang
Social network alignment has been an important research problem for social network analysis in recent years. With the identified shared users across networks, it will provide resea…
Heterogeneous Deep Graph Infomax
Yuxiang Ren, Bo Liu, Chao Huang +3
Graph representation learning is to learn universal node representations that preserve both node attributes and structural information. The derived node representations can be used…
JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation
Zhiwei Liu, Lei Zheng, Jiawei Zhang +2
Cross-domain recommendation can alleviate the data sparsity problem in recommender systems. To transfer the knowledge from one domain to another, one can either utilize the neighbo…
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…
GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation
Jiawei Zhang, Lin Meng
The existing graph neural networks (GNNs) based on the spectral graph convolutional operator have been criticized for its performance degradation, which is especially common for th…
BGADAM: Boosting based Genetic-Evolutionary ADAM for Neural Network Optimization
Jiyang Bai, Yuxiang Ren, Jiawei Zhang
For various optimization methods, gradient descent-based algorithms can achieve outstanding performance and have been widely used in various tasks. Among those commonly used algori…
Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview
Jiawei Zhang
Graph neural networks denote a group of neural network models introduced for the representation learning tasks on graph data specifically. Graph neural networks have been demonstra…
DEAM: Adaptive Momentum with Discriminative Weight for Stochastic Optimization
Jiyang Bai, Yuxiang Ren, Jiawei Zhang
Optimization algorithms with momentum, e.g., (ADAM), have been widely used for building deep learning models due to the faster convergence rates compared with stochastic gradient d…
Graph Neural Lasso for Dynamic Network Regression
Yixin Chen, Lin Meng, Jiawei Zhang
The regression of multiple inter-connected sequence data is a problem in various disciplines. Formally, we name the regression problem of multiple inter-connected data entities as…
IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification
Lin Meng, Jiawei Zhang
Deep learning models have achieved huge success in numerous fields, such as computer vision and natural language processing. However, unlike such fields, it is hard to apply tradit…
Missing Movie Synergistic Completion across Multiple Isomeric Online Movie Knowledge Libraries
Bowen Dong, Jiawei Zhang, Chenwei Zhang +2
Online knowledge libraries refer to the online data warehouses that systematically organize and categorize the knowledge-based information about different kinds of concepts and ent…
Derivative-Free Global Optimization Algorithms: Population based Methods and Random Search Approaches
Jiawei Zhang
In this paper, we will provide an introduction to the derivative-free optimization algorithms which can be potentially applied to train deep learning models. Existing deep learning…
Derivative-Free Global Optimization Algorithms: Bayesian Method and Lipschitzian Approaches
Jiawei Zhang
In this paper, we will provide an introduction to the derivative-free optimization algorithms which can be potentially applied to train deep learning models. Existing deep learning…
Gradient Descent based Optimization Algorithms for Deep Learning Models Training
Jiawei Zhang
In this paper, we aim at providing an introduction to the gradient descent based optimization algorithms for learning deep neural network models. Deep learning models involving mul…
Meta Diagram based Active Social Networks Alignment
Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang
Network alignment aims at inferring a set of anchor links matching the shared entities between different information networks, which has become a prerequisite step for effective fu…