Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
In this paper we explore some of the connections between cooperative game theory and the utility maximization framework for routing and flow control in networks. Central to both a...
In data mining, similarity or distance between attributes is one of the central notions. Such a notion can be used to build attribute hierarchies etc. Similarity metrics can be us...
Prior distributions are useful for robust low-level vision, and undirected models (e.g. Markov Random Fields) have become a central tool for this purpose. Though sometimes these p...