Mixed Membership Sparse Gaussian Conditional Random Fields

Jie Yang; Henry C. M. Leung; Siu‐Ming Yiu; Francis Y. L. Chin

doi:10.1007/978-3-319-69179-4_20

ScienceGate Book Chapters

BOOK-CHAPTER

Mixed Membership Sparse Gaussian Conditional Random Fields

Jie Yang Henry C. M. Leung Siu‐Ming Yiu Francis Y. L. Chin

Year: 2017 Lecture notes in computer science Pages: 287-302 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-69179-4_20

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Gaussian Conditional random field Degree (music) Association (psychology) Expectation–maximization algorithm Bayesian probability Artificial intelligence Set (abstract data type) Algorithm Field (mathematics) Pattern recognition (psychology) Data mining Machine learning Mathematics Statistics Maximum likelihood

Metrics

Cited By

0.29

FWCI (Field Weighted Citation Impact)

Refs

0.57

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Gaussian Processes and Bayesian Inference

Physical Sciences → Computer Science → Artificial Intelligence

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Mixed Membership Sparse Gaussian Conditional Random Fields

Metrics

Citation History

Topics

Related Documents

Wireless Channel Quality Prediction using Sparse Gaussian Conditional Random Fields

Neural Gaussian Conditional Random Fields

Sparse Gaussian Conditional Random Fields on Top of Recurrent Neural Networks

Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting

Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting