Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
The binary representation is widely used for representing focal sets of Dempster-Shafer belief functions because it allows to compute efficiently all relevant operations. However, ...
—Based on a recent view of Pstable models that allows talking about knowledge and beliefs of an agent, we propose an extension of the AGM postulates based on these notions. To th...
Fernando Zacarias Flores, Mauricio Osorio Galindo,...
We introduce a framework for syntactic parsing with latent variables based on a form of dynamic Sigmoid Belief Networks called Incremental Sigmoid Belief Networks. We demonstrate ...
We introduce a simple asset pricing model with two types of adaptively learning traders, fundamentalists and technical traders. Traders update their beliefs according to past perfo...