We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Importance sampling is a popular approach to estimate rare event failures of SRAM cells. We propose to improve importance sampling by probability collectives. First, we use “Kul...
Fang Gong, Sina Basir-Kazeruni, Lara Dolecek, Lei ...