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基于贝叶斯网络的半监督聚类集成模型
- 已有的聚类集算法基本上都是非监督聚类集成算法,这样不能利用已知信息,使得聚类集成的准确性、鲁棒性和稳定性降低.把半监督学习和聚类集成结合起来,设计半监督聚类集成模型来克服这些缺点.主要工作包括:第一,设计了基于贝叶斯网络的半监督聚类集成(semi-supervised cluster ensemble,简称SCE)模型,并对模型用变分法进行了推理求解;第二,在此基础上,给出了EM(expectation maximization)框架下的具体算法;第三,从UCI(University of Ca
opencv em算法
- Expectation-Maximization The EM (Expectation-Maximization) algorithm estimates the parameters of the multivariate probability density function in a form of the Gaussian mixture distribution with a specified number of mixtures.
GMM
- Source code - create Gaussian Mixture Model in following steps: 1, K-means 2, Expectation-Maxximization 3, GMM Notice: All datapoints are generated randomly and you can config in Config.h-Source code- create Gaussian Mixture Model
empca
- I present an expectation-maximization (EM) algorithm for principal component analysis (PCA).
registration_EM
- It actually simulates the registration process of multiple dissimilar sensors in a wireless sensor network using the expectation maximization algorithm.
iccsa06_1
- Expectation-maximization algorithm
Ch04
- Expectation-maximization algorithm
Ch05
- Expectation-maximization algorithm
modelbasedonspectrumprediction
- 文章展示了基于高斯混合模型的语音频谱预测方法。频谱预测可能在传包过程中预防丢包这方面起到大作用。期望最大化算法用两倍或三倍的连续语音因素来测试模型。模型被用来设计第一，儿等指令预测量。预测表用频谱分配状态来估计并和一个简单的参考模型对比。最好的预测表得到一个平均频率扭曲值是0.46dB小于参考模型-This paper presents methods for speech spectrum prediction based on Gaussian mixture models. Spec
EM_algorithm.pdf
- Good tutorial for Expectation maximization algorithm
A-Bayesian-Approach
- In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth’s crust.We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution
eScholarship-UC-item-1rb70972
- Expectation maximization and mixture model tutorial
WEALTH-MAXIMIZATION-OBJECTIVE-IS-SUPERIOR-TO-THE-
- This the most important book-This is the most important book
Fergus-Perona
- We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constellations of parts. A probabilistic representation is used for al
New-Beamforming-Techniques-Based-on-Virtual-SINR.
- New Beamforming Techniques Based on Virtual SINR Maximization for Coordinated Multi-Cell Transmission
ERP
- ERP系统是指建立在信息技术基础上，以系统化的管理思想，为企业决策层及员工提供决策运行手段的管理平台。它是从MRP（物料需求计划）发展而来的新一代集成化管理信息系统，它扩展了MRP的功能，其核心思想是供应链管理。它跳出了传统企业边界，从供应链范围去优化企业的资源。ERP系统集信息技术与先进管理思想于一身，成为现代企业的运行模式，反映时代对企业合理调配资源，最大化地创造社会财富的要求，成为企业在信息时代生存、发展的基石。它对于改善企业业务流程、提高企业核心竞争力具有显著作用。-ERP system
Km
- In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Vo
Gupta-and-Chen---2010---Theory
- This introduction to the expectation–maximization (EM) algorithm provides an intuitive and mathematically rigorous understanding of EM. Two of the most popular applications of EM are described in detail: estimating Gaussian mixture models (GMMs),
Best-2---2012
- Sum-Rate Maximization in Two-Way AF MIMO Relaying: Polynomial Time Solutions to a Class of DC Programming Problems
Wind-Speed-Estimation
- Wind Speed Estimation Based Sensorless Output Maximization Control for a Wind Turbine Driving a DFI