Probabilistic

Probabilistic Voting Model
... The probabilistic voting theory, also known as the probabilistic voting model, is a voting theory developed by professor Melvin Hinich, which has gradually replaced the median voter theory, thanks to its ... The probabilistic voting model assumes that voters are imperfectly informed about candidates and their platforms ...

Probabilistic Design
... Probabilistic design is a discipline within engineering design ... Thus, probabilistic design is a tool that is mostly used in areas that are concerned with quality and reliability ...

Lateral Computing - A Review of Lateral-computing Techniques - Probabilistic/chaotic Computing
... Probabilistic computing engines, e.g ... use of probabilistic graphical model such as Bayesian network ... Such computational techniques are referred to as randomization, yielding probabilistic algorithms ...

Statistical Relational Learning
... of a domain in a general manner (universal quantification) and draw upon probabilistic graphical models (such as Bayesian networks or Markov networks) to model the uncertainty some also build upon the methods of ... limited to learning aspects it is equally concerned with reasoning (specifically probabilistic inference) and knowledge representation ... relational learning and reasoning (emphasizing the importance of reasoning) and first-order probabilistic languages (emphasizing the key properties of the languages ...

Stochastic Grammar
... grammar) is a grammar framework with a probabilistic notion of grammaticality Stochastic context-free grammar Statistical parsing Data-oriented parsing Hidden Markov model Estimation theory ... "A probabilistic model consists of a non-probabilistic model plus some numerical quantities it is not true that probabilistic models are inherently simpler or less structural than non-probabilistic models." ...