Recommendation is one of the critical applications that helps users find...
Studies show that the representations learned by deep neural networks ca...
Limited labeled data is becoming the largest bottleneck for supervised
l...
Network representation learning, a fundamental research problem which ai...
Synthesizing geometrical shapes from human brain activities is an intere...
Online users generate tremendous amounts of textual information by
parti...
With convenient access to observational data, learning individual causal...
Floods of research and practical applications employ social media data f...
Symbolic Aggregate approximation (SAX) is a classical symbolic approach ...
Consuming news from social media is becoming increasingly popular. Socia...
The increasing popularity and diversity of social media sites has encour...
Predicting signed links in social networks often faces the problem of si...
Online learning with limited information feedback (bandit) tries to solv...
The overturning of the Internet Privacy Rules by the Federal Communicati...
The era of big data provides researchers with convenient access to copio...
As opposed to manual feature engineering which is tedious and difficult ...
Modeling spillover effects from observational data is an important probl...
The increasing popularity of social media has attracted a huge number of...
Learning expressive low-dimensional representations of ultrahigh-dimensi...
Social media users generate tremendous amounts of data. To better serve
...
The pervasive use of social media provides massive data about individual...
Most social media platforms are largely based on text, and users often w...
The parameters in a nuclear magnetic resonance (NMR) free induction deca...
Social media for news consumption is a double-edged sword. On the one ha...
Network embedding leverages the node proximity manifested to learn a
low...
Sentiment in social media is increasingly considered as an important res...
Many real-world relations can be represented by signed networks with pos...