—Online learning algorithms often have to operate in the presence of concept drifts. A recent study revealed that different diversity levels in an ensemble of learning machines a...
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
We develop a cyclical blockwise coordinate descent algorithm for the multi-task Lasso that efficiently solves problems with thousands of features and tasks. The main result shows ...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...