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Minka s Bayes Point Machine.
Applying Expectation Propagation to inference.
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Thomas Minka 编写的适用于Bayesian Point Machine，Expectation Propagation计算的matlab工具箱。对科研人员很有价值。
-This toolbox implements the EP algorithms described in Thomas Minka s thesis and UAI paper.
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Pattern recognition has its origins in engineering, whereas machine learning grew
out of computer science. However, these activities can be viewed as two facets of
the same field, and together they have undergone substantial development over the
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输入学习样本，使用反向传播算法对网络的权值和偏差进行反复的调整训练，使输出的向量与期望向量尽可能地接近，当网络输出层的误差平方和小于指定的误差时训练完成，保存网络的权值和偏差。-Enter the study sample, using the back-propagation algorithm repeatedly adjust training of the network weights and deviation as close as possible, so that the ou
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用多尺度卡尔曼滤波法，对信号参数进行识别估计。高频信号和低频信号识别结合起来改进了算法识别的精确度和准确度。-It is an implementation of hierarchical (a.k.a. multi-scale) Kalman filter using belief propagation. The model parameters are estimated by expectation maximization (EM) algorithm. In this impleme
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Matlab环境下基于期望传播算法的贝叶斯分类器工具箱-Matlab environment based on the expectation propagation algorithm toolbox Bayesian classifier
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在客户端和服务器通过套接字连接设计分布式逻辑回归模型。该服务器可以处理用户的使用预定义的用户名和密码验证。该框架提供了用于保护敏感信息的高层次的保证，由于信息服务器之间交换和客户端是系数的后验分布。-We design a distributed logistic regression model using expectation propagation, where clients and server are connected through sockets. The server ca
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