We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
In this paper, we propose a new application of Bayesian language model based on Pitman-Yor process for information retrieval. This model is a generalization of the Dirichlet distr...
The ROMIO implementation of the MPI-IO standard provides a portable infrastructure for use on top of a variety of underlying storage targets. These targets vary widely in their ca...
In this paper, we present a variational Bayesian (VB) approach to computing the interval estimates for nonhomogeneous Poisson process (NHPP) software reliability models. This appr...
Hiroyuki Okamura, Michael Grottke, Tadashi Dohi, K...
The ability to account for the growing impacts of multiple process variations in modern technologies is becoming an integral part of nanometer VLSI design. Under the context of ti...