68 citations · 203 across the 30 of their papers we have counts for
4 papers · 1 filter
Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction
Yikai Wang, Liang Zhang, Quanyu Dai +5
Improving the performance of click-through rate (CTR) prediction remains one of the core tasks in online advertising systems. With the rise of deep learning, CTR prediction models…
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs
Qimai Li, Xiaotong Zhang, Han Liu +2
Graph convolutional neural networks (GCN) have been the model of choice for graph representation learning, which is mainly due to the effective design of graph convolution that com…
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
Quanyu Dai, Xiao-Ming Wu, Jiaren Xiao +2
This paper studies the problem of cross-network node classification to overcome the insufficiency of labeled data in a single network. It aims to leverage the label information in…
Adversarial Training Methods for Network Embedding
Quanyu Dai, Xiao Shen, Liang Zhang +2
Network Embedding is the task of learning continuous node representations for networks, which has been shown effective in a variety of tasks such as link prediction and node classi…