We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
This paper explores the addition of constraints to the linear programming formulation of the support vector regression problem for the incorporation of prior knowledge. Equality an...
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
Bharath K. Sriperumbudur, David A. Torres, Gert R....
We investigate the results of coevolution of spatially distributed populations. In particular, we describe work in which a simple function approximation problem is used to compare...
We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm desi...