Handbook of mixed membership models and their applications / edited by Edoardo M. Airoldi, David Blei, Elena A. Erosheva, Stephen E. Fienberg.

In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling t...

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Bibliographic Details
Online Access: Full Text (via ProQuest)
Other Authors: Airoldi, Edoardo (Editor), Blei, David (Editor), Erosheva, Elena A. (Elena Aleksandrovna) (Editor), Fienberg, Stephen E. (Editor)
Format: eBook
Language:English
Published: Boca Raton : Chapman & Hall/CRC, 2014.
Series:Chapman & Hall/CRC handbooks of modern statistical methods.
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505 0 |a Front Cover; Contents; Preface; Editors; Contributors; List of Figures; List of Tables; Part 1 Mixed Membership: Setting the Stage; Chapter 1 Introduction to Mixed Membership Models and Methods; Chapter 2 A Tale of Two (Types of) Memberships: Comparing Mixed and Partial Membership with a Continuous Data Example; Chapter 3 Interpreting Mixed Membership Models: Implications of Erosheva's Representation Theorem; Chapter 4 A Simple and General Exponential Family Framework for Partial Membership and Factor Analysis; Chapter 5 Nonparametric Mixed Membership Models. 
505 8 |a Part 2 The Grade of Membership Model and Its ExtensionsChapter 6 A Mixed Membership Approach to the Assessment of Political Ideology from Survey Responses; Chapter 7 Estimating Diagnostic Error without a Gold Standard: A Mixed Membership Approach; Chapter 8 Interpretability Constraints and Trade- offs in Using Mixed Membership Models; Chapter 9 Mixed Membership Trajectory Models; Chapter 10 An Analysis of Development of Dementia through the Extended Trajectory Grade of Membership Model; Part 3 Topic Models: Mixed Membership Models for Text. 
505 8 |a Chapter 11 Bayesian Nonnegative Matrix Factorization with Stochastic Variational InferenceChapter 12 Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements; Chapter 13 Block- LDA: Jointly Modeling Entity- Annotated Text and Entity- Entity Links; Chapter 14 Robust Estimation of Topic Summaries Leveraging Word Frequency and Exclusivity; Part 4 Semi- Supervised Mixed Membership Models; Chapter 15 Mixed Membership Classification for Documents with Hierarchically Structured Labels; Chapter 16 Discriminative Mixed Membership Models. 
505 8 |a Chapter 17 Mixed Membership Matrix FactorizationDiscriminative Training of Mixed Membership Models; Part 5 Special Methodology for Sequence and Rank Data; Chapter 19 Population Stratification with Mixed Membership Models; Chapter 20 Mixed Membership Models for Time Series; Chapter 21 Mixed Membership Models for Rank Data: Investigating Structure in Irish Voting Data; Part 6 Mixed Membership Models for Networks; Chapter 22 Hierarchical Mixed Membership Stochastic Blockmodels for Multiple Networks and Experimental Interventions. 
505 8 |a Chapter 23 Analyzing Time- Evolving Networks using an Evolving Cluster Mixed Membership BlockmodelChapter 24 Mixed Membership Blockmodels for Dynamic Networks with Feedback; Chapter 25 Overlapping Clustering Methods for Networks; Back Cover. 
520 |a In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, yo. 
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