Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
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...
We present an algorithm for detecting human actions
based upon a single given video example of such actions.
The proposed method is unsupervised, does not require
learning, segm...
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...