Processing Probabilistic and Deterministic Graphical Models
نویسنده
چکیده
منابع مشابه
Probabilistic Resolution: an Anytime Bounded Approximation Inference Algorithm for Graphical Models
Graphical models are the most prominent probabilistic inference framework in recent AI. They generalize deterministic logical propositional reasoning, which presents the important property of not requiring the processing of an entire theory for solving a query, but only its relevant parts. This property is lost in the generalization to graphical models since the entire model typically becomes r...
متن کاملImplicational Scaling of Reading Comprehension Construct: Is it Deterministic or Probabilistic?
In English as a Second Language Teaching and Testing situations, it is common to infer about learners’ reading ability based on his or her total score on a reading test. This assumes the unidimensional and reproducible nature of reading items. However, few researches have been conducted to probe the issue through psychometric analyses. In the present study, the IELTS exemplar module C (1994) wa...
متن کاملRule-based joint fuzzy and probabilistic networks
One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...
متن کاملReasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms
It's not surprisingly when entering this site to get the book. One of the popular books now is the reasoning with probabilistic and deterministic graphical models exact algorithms rina dechter. You may be confused because you can't find the book in the book store around your city. Commonly, the popular book will be sold quickly. And when you have found the store to buy the book, it will be so h...
متن کاملMixtures of Deterministic-Probabilistic Networks and their AND/OR Search Space
The paper introduces mixed networks, a new framework for expressing and reasoning with probabilistic and deterministic information. The framework combines belief networks with constraint networks, defining the semantics and graphical representation. We also introduce the AND/OR search space for graphical models, and develop a new linear space search algorithm. This provides the basis for unders...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013