Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction ...
As learning environments become increasingly available online, the fine-grained records of user activities can be captured and analyzed (generally called webmetrics) to better unde...
The article offers a new approach towards the construction of recognition features independent of images' displacement or linear deformation. The distinguishing characteristi...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
It is well known that many hard tasks considered in machine learning and data mining can be solved in an rather simple and robust way with an instance- and distance-based approach....