In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
The application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. Based on the Expectation Regularization...
Semi-supervised clustering allows a user to specify available prior knowledge about the data to improve the clustering performance. A common way to express this information is in ...
Georeferenced information is growing every day, and geographical information systems are becoming crucial in many decision processes. As a consequence, extracting knowledge from G...
A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcemen...