This paper presents an efficient algorithm for image segmentation and a framework for perceptual grouping. It makes an attempt to provide one way of combining bottomup and top-do...
Real-world databases often contain syntactic and semantic errors, in spite of integrity constraints and other safety measures incorporated into modern DBMSs. We present ERACER, an...
We study the problem of estimating selectivity of approximate substring queries. Its importance in databases is ever increasing as more and more data are input by users and are in...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
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...