**A Survey of Statistical Network Models**

by A. Goldenberg, A.X. Zheng, S.E. Fienberg, E.M. Airoldi

**Publisher**: arXiv 2009**ISBN/ASIN**: 1601983204**ISBN-13**: 9781601983206**Number of pages**: 96

**Description**:

We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation.

Download or read it online for free here:

**Download link**

(1.7MB, PDF)

## Similar books

**Statistical Foundations of Machine Learning**

by

**Gianluca Bontempi, Souhaib Ben Taieb**-

**OTexts**

This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice.

(

**3946**views)

**Introduction To Machine Learning**

by

**Nils J Nilsson**

This book concentrates on the important ideas in machine learning, to give the reader sufficient preparation to make the extensive literature on machine learning accessible. The author surveys the important topics in machine learning circa 1996.

(

**18948**views)

**A Course in Machine Learning**

by

**Hal DaumÃ© III**-

**ciml.info**

Tis is a set of introductory materials that covers most major aspects of modern machine learning (supervised and unsupervised learning, large margin methods, probabilistic modeling, etc.). It's focus is on broad applications with a rigorous backbone.

(

**10313**views)

**Practical Artificial Intelligence Programming in Java**

by

**Mark Watson**-

**Lulu.com**

The book uses the author's libraries and the best of open source software to introduce AI (Artificial Intelligence) technologies like neural networks, genetic algorithms, expert systems, machine learning, and NLP (natural language processing).

(

**16821**views)