Recent research has found that diagnostic performance with Bayesian belief networks is often surprisingly insensitive to imprecision in the numerical probabilities. For example, t...
Max Henrion, Malcolm Pradhan, Brendan Del Favero, ...
Abstract--Fault localization in enterprise networks is extremely challenging. A recent approach called Sherlock makes some headway into this problem by using an inference algorithm...
– The main task of a voice-enabled tour-guide robot in mass exhibition setting is to engage visitors in dialogue and provide as much exhibit information as possible in a limited ...
During past few years, a variety of methods have been developed for learning probabilistic networks from data, among which the heuristic single link forward or backward searches ar...
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...