In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Background: Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene produc...