Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
Web-Streaming lectures overcome the space and time barriers between learning and teaching, but bring higher requirements on the learning feedback of students when they browse lectu...
This paper presents varifold learning, a learning framework based on the mathematical concept of varifolds. Different from manifold based methods, our varifold learning framework ...
In the web context, it is difficult to disentangle presentation from process logic, and sometimes even data is not separate from the presentation. Consequently, it becomes to de...
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...