Advances in Probabilistic Graphical Models
- المؤلف
- Peter Lucas, José A. Gámez, Antonio Salmerón
- سنة النشر
- 2007
- الناشر
- Springer
- لغة الملف
- انكليزي
- نوع الملف
- Book
- تصنيف الكتاب
- Engineering
- تحميل الكتاب قراءة الكتاب
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
الكلمات المفتاحية: Engineering / Bayesian network / Graph / Markov / Probability distribution / Triangulation / Algorithms / Artificial intelligence / Autonom / Bioinformatics / Classification / Learning / Modelling / Probabilistic network / Statistics / Uncertainty
