## Home > Tags: probabilistic (Total 46 Records)

### Probabilistic Approaches to Recommendations (Synthesis Lectures on Data Mining and Knowledge Discovery)

Computer Science By:Nicola Barbieri 2014-06-01 00:00:00

The importance of accurate recommender systems has been widely recognized by academia and industry, and recommendation is rapidly becoming one of the most successful applications of data mining and machine learning. Understanding and predicting the choices and preferences of users is a challenging t Computer Science

Tags:
*data*
*approach*
*lecture*
*synthesis*
*mining*
*knowledge*
*discovery*
*probabilistic*

### Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms (Synthesis Lectures on Artificial Intelligence and Machine Learning)

Algorithms By:Rina Dechter 2013-12-01 00:00:00

Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning task Algorithms

Tags:
*algorithm*
*model*
*learning*
*lecture*
*machine*
*synthesis*
*intelligence*
*artificial*
*graphical*
*reasoning*
*probabilistic*
*deterministic*
*exact*

### Building Probabilistic Graphical Models with Python

Computer Science By:Kiran R Karkera 2014-05-25 00:00:00

Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications Overview Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image proce graphical models, probabilistic graphical models, building probabilistic graphical, python libraries, field.building probabilistic graphical

Tags:
*model*
*python*
*graphical*
*probabilistic*

### Modeling and Analysis of Dependable Systems: A Probabilistic Graphical Model Perspective

Computer Science By:Luigi Portinale 2015-07-24 00:00:00

The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts a probabilistic graphical model, graphical model perspective, standard dependability formalisms, probabilistic graphical models, dependable systems

Tags:
*analysis*
*system*
*model*
*perspective*
*graphical*
*probabilistic*
*dependable*

### Learning Probabilistic Graphical Models in R

Computer Science By:David Bellot 2016-04-29 00:00:00

Key Features Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Book Descripti probabilistic graphical models, learning probabilistic graphical, powerful probabilistic model, bayesian linear regression, approximate inference algorithms

Tags:
*model*
*learning*
*graphical*
*probabilistic*

### Semantics of Probabilistic Processes: An Operational Approach

Programming By:Yuxin Deng 2015-02-06 00:00:00

This book discusses the semantic foundations of concurrent systems with nondeterministic and probabilistic behaviour. Particular attention is given to clarifying the relationship between testing and simulation semantics and characterising bisimulations from metric, logical, and algorithmic perspecti probabilistic concurrency theory, probabilistic processes, operational approach, probabilistic behaviour, semantic foundations

### Practical Probabilistic Programming

Programming By:Avi Pfeffer 2016-05-01 00:00:00

Data accumulated about customers, products, and website users can not only help interpret the past, it can help predict the future! Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, progra probabilistic programming, practical probabilistic programming, probabilistic models, campaign.practical probabilistic programming, social media usage

Tags:
*programming*
*probabilistic*

### Building Probabilistic Graphical Models with Python

Programming By:Kiran R Karkera 2014-05-25 00:00:00

Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications Overview Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image proce graphical models, probabilistic graphical models, building probabilistic graphical, field.building probabilistic graphical, python libraries

Tags:
*model*
*python*
*graphical*
*probabilistic*

### Design and Analysis of Learning Classifier Systems: A Probabilistic Approach (Studies in Computational Intelligence)

Computer Science By:Jan Drugowitsch 2008-05-30 00:00:00

This book provides a comprehensive introduction to the design and analysis of Learning Classifier Systems (LCS) from the perspective of machine learning. LCS are a family of methods for handling unsupervised learning, supervised learning and sequential decision tasks by decomposing larger problem sp learning classifier systems, prominent xcs classifier, lcs algorithms, probabilistic model-based approach, probabilistic approach

Tags:
*design*
*study*
*analysis*
*system*
*computational*
*approach*
*learning*
*intelligence*
*probabilistic*
*classifier*

### Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

Robotics By:Sebastian Thrun 2005-08-19 00:00:00

Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the re probabilistic robotics, autonomous agents series, real-world sensor data., detailed mathematical derivations, robotic software development