This paper proposes a method of integrating two different concepts of belief in artificial intelligence: belief as a probability distribution and belief as a logical formula. The...
We show how to use linear belief functions to represent market information and financial knowledge, including complete ignorance, statistical observations, subjective speculations...
We propose consensus propagation, an asynchronous distributed protocol for averaging numbers across a network. We establish convergence, characterize the convergence rate for regul...
There are many local and greedy algorithms for energy minimization over Markov Random Field (MRF) such as iterated condition mode (ICM) and various gradient descent methods. Local ...
A parallel distributed computational model for reasoning and learning is discussed based on a belief network paradigm. Issues like reasoning and learning for the proposed model ar...