In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
We study the problem of simultaneously estimating several densities where the datasets are organized into overlapping groups, such as a hierarchy. For this problem, we propose a m...
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...
In recent years, privacy preserving data mining has become an important problem because of the large amount of personal data which is tracked by many business applications. In many...