79 citations · 583 across the 45 of their papers we have counts for
11 papers · 1 filter
Discrete Auto-regressive Variational Attention Models for Text Modeling
Xianghong Fang, Haoli Bai, Jian Li +3
Variational autoencoders (VAEs) have been widely applied for text modeling. In practice, however, they are troubled by two challenges: information underrepresentation and posterior…
FeatureNorm: L2 Feature Normalization for Dynamic Graph Embedding
Menglin Yang, Ziqiao Meng, Irwin King
Dynamic graphs arise in a plethora of practical scenarios such as social networks, communication networks, and financial transaction networks. Given a dynamic graph, it is fundamen…
Graph-based Semi-supervised Learning: A Comprehensive Review
Zixing Song, Xiangli Yang, Zenglin Xu +1
Semi-supervised learning (SSL) has tremendous value in practice due to its ability to utilize both labeled data and unlabelled data. An important class of SSL methods is to natural…
AutoGraph: Automated Graph Neural Network
Yaoman Li, Irwin King
Graphs play an important role in many applications. Recently, Graph Neural Networks (GNNs) have achieved promising results in graph analysis tasks. Some state-of-the-art GNN models…
Effective Data-aware Covariance Estimator from Compressed Data
Xixian Chen, Haiqin Yang, Shenglin Zhao +2
Estimating covariance matrix from massive high-dimensional and distributed data is significant for various real-world applications. In this paper, we propose a data-aware weighted…
Making Online Sketching Hashing Even Faster
Xixian Chen, Haiqin Yang, Shenglin Zhao +2
Data-dependent hashing methods have demonstrated good performance in various machine learning applications to learn a low-dimensional representation from the original data. However…