The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate...
Data visualization, commonly used to make large sets of numerical data more legible, also has enormous potential as a storytelling tool to elicit insights on long-standing social ...
The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming a...
We report on a study that was undertaken to better identify users' goals behind web search queries by using click through data. Based on user logs which contain over 80 millio...