114 citations · 255 across the 12 of their papers we have counts for
5 papers · 1 filter
From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction
Han Xiao, Minlie Huang, Xiaoyan Zhu
Knowledge graph embedding aims at offering a numerical knowledge representation paradigm by transforming the entities and relations into continuous vector space. However, existing…
TransA: An Adaptive Approach for Knowledge Graph Embedding
Han Xiao, Minlie Huang, Yu Hao +1
Knowledge representation is a major topic in AI, and many studies attempt to represent entities and relations of knowledge base in a continuous vector space. Among these attempts,…
TransG : A Generative Mixture Model for Knowledge Graph Embedding
Han Xiao, Minlie Huang, Yu Hao +1
Recently, knowledge graph embedding, which projects symbolic entities and relations into continuous vector space, has become a new, hot topic in artificial intelligence. This paper…
Margin-Based Feed-Forward Neural Network Classifiers
Han Xiao, Xiaoyan Zhu
Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical an…
Max-Entropy Feed-Forward Clustering Neural Network
Han Xiao, Xiaoyan Zhu
The outputs of non-linear feed-forward neural network are positive, which could be treated as probability when they are normalized to one. If we take Entropy-Based Principle into c…