Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algor...
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...