Guodong Long

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DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding

Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang
AAAI
2018

Recurrent neural nets (RNN) and convolutional neural nets (CNN) are widely used on NLP tasks to capture the long-term and local dependencies, respectively. Attention mechanisms have recently… (More)

Scaling-Up Item-Based Collaborative Filtering Recommendation Algorithm Based on Hadoop

Jing Jiang, Jie Lu, Guangquan Zhang, Guodong Long
IEEE World Congress on Services
2011

Collaborative filtering (CF) techniques have achieved widespread success in E-commerce nowadays. The tremendous growth of the number of customers and products in recent years poses some key… (More)

Optimal Cloud Resource Auto-Scaling for Web Applications

Jing Jiang, Jie Lu, Guangquan Zhang, Guodong Long
13th IEEE/ACM International Symposium on Cluster…
2013

In the on-demand cloud environment, web application providers have the potential to scale virtual resources up or down to achieve cost-effective outcomes. True elasticity and cost-effectiveness in… (More)

Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling

Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang
ICLR
2018

Recurrent neural networks (RNN), convolutional neural networks (CNN) and selfattention networks (SAN) are commonly used to produce context-aware representations. RNN can capture long-range dependency… (More)

Adversarially Regularized Graph Autoencoder for Graph Embedding

Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang
IJCAI
2018

Graph embedding is an effective method to represent graph data in a low dimensional space for graph analytics. Most existing embedding algorithms typically focus on preserving the topological… (More)

Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling

Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang
IJCAI
2018

Many natural language processing tasks solely rely on sparse dependencies between a few tokens in a sentence. Soft attention mechanisms show promising performance in modeling local/global… (More)

Global and Local Influence-based Social Recommendation

Qinzhe Zhang, Jia Wu, Hong Yang, Weixue Lu, Guodong Long, Chengqi Zhang
CIKM
2016

Social recommendation has been widely studied in recent years. Existing social recommendation models use various explicit pieces of social information as regularization terms in recommendation, for… (More)

Dynamic Concept Composition for Zero-Example Event Detection

Xiaojun Chang, Yi Yang, Guodong Long, Chengqi Zhang, Alexander G. Hauptmann
AAAI
2016

In this paper, we focus on automatically detecting events in unconstrained videos without the use of any visual training exemplars. In principle, zero-shot learning makes it possible to train an… (More)

Task Sensitive Feature Exploration and Learning for Multitask Graph Classification

Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang
IEEE Transactions on Cybernetics
2017

Multitask learning (MTL) is commonly used for jointly optimizing multiple learning tasks. To date, all existing MTL methods have been designed for tasks with feature-vector represented instances, but… (More)

Universal network representation for heterogeneous information networks

Ruiqi Hu, Celina Ping Yu, Sai-Fu Fung, Shirui Pan, Haishuai Wang, Guodong Long
International Joint Conference on Neural Networks…
2017

Network representation aims to represent the nodes in a network as continuous and compact vectors, and has attracted much attention in recent years due to its ability to capture complex structure… (More)

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