We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
ibe an abstract data model of protein structures by representing the geometry of proteins using spatial data types and present a framework for fast structural similarity search bas...
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Estimating the arrival rate function of a non-homogeneous Poisson process based on observed arrival data is a problem naturally arising in many applications. Cubic spline function...
Farid Alizadeh, Jonathan Eckstein, Nilay Noyan, G&...
Assume a network (V, E) where a subset of the nodes in V are active. We consider the problem of selecting a set of k active nodes that best explain the observed activation state, ...