In this paper, we present a novel technique for modeling the posterior probability estimates obtained from a neural network directly in the HMM framework using the Dirichlet Mixtu...
Balakrishnan Varadarajan, Garimella S. V. S. Sivar...
Importance sampling is used in this paper to address the classical yet important problem of performance estimation of block codes. Simulation distributions that comprise discretean...
Abstract. A resource selection probability function is a function that gives the probability that a resource unit (e.g., a plot of land) that is described by a set of habitat varia...
In this paper we extend an earlier worst case bound reliability theory to derive a worst case reliability function R(t), which gives the worst case probability of surviving a furt...
Good-Turing adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in tha...