We propose a simple and effective embedding model, named QuatRE, to lear...
We consider reducing model parameters and moving beyond the Euclidean sp...
Despite several signs of progress have been made recently, limited resea...
In this paper, we focus on learning low-dimensional embeddings of entity...
Existing graph embedding models often have weaknesses in exploiting grap...
Knowledge graph embedding models often suffer from a limitation of
remem...
In this paper, we introduce an embedding model, named CapsE, exploring a...
Abnormal event detection is one of the important objectives in research ...
Search personalization aims to tailor search results to each specific us...
We introduce a novel embedding method for knowledge base completion task...
Generative Adversarial Networks (GANs) were intuitively and attractively...
Some real-world problems revolve to solve the optimization problem
_x∈Xf...
We propose in this paper a novel approach to tackle the problem of mode
...
The analysis of mixed data has been raising challenges in statistics and...
Training model to generate data has increasingly attracted research atte...
We propose a new approach to train the Generative Adversarial Nets (GANs...
One of the most challenging problems in kernel online learning is to bou...