Semantic Information Theory with CM Algorithm for Machine Learning: Chenguang Lu's Recent  Papers

鲁晨光最近文章——语义信息论和信道匹配算法用于机器学习

时间 Time 中文 PPT 说明 English PPT Note
2018 EM算法的问题和出路  CM4Mix 包括更严格收敛证明 示范文件 From EM algorithm to CM-EM algorithm for global convergence of mixture models CM4Mix With strict convergence proof
Demo files
uploaded to Arxiv.org
2008 从贝叶斯推理到逻辑贝叶斯推理——一个新的数学框架用于语义通信和机器学习   阶段总结,右边是英文缩写 From Bayesian Inference to Logical Bayesian Inference: A New Mathematical Frame for Semantic Communication and Machine Learning New-Frame ICIS2018
2008 求标签外延和最大语义信息分类
多标签学习和分类浅谈——从语义通信角度看
CM4Ml 中英文不同,包括补充解释 Semantic Channel and Shannon’s Channel Mutually Match for Multi-label Classification CM4Mlabel ICIS2018
2018 第三种贝叶斯定理用于语义通信和机器学习 右边是英文缩写 The Third Kind of Bayes’ Theorem Links Membership Functions to Likelihood Functions and Sampling Distributions ICCSIP2018
2018 语义信道和Shannon信道相互匹配求检验和估计的最大互信息和最大似然度    示范文件 Semantic channel and Shannon channel mutually match and iterate for tests and estimations with Maximum mutual information and maximum likelihood CM4MMI-ppt Demo files
IEEE Int. Conf. on Big Data & Smart Comp.- 2018 
2017 信道匹配算法用于混合模型(见英文)     Channels' Matching Algorithm for Mixture Models Cm4mix.ppt ICIS2017
2017 兼容Shannon,Popper, Fisher, and Zadeh思想的语义信息方法(见英文) Compatible   The semantic information methods compatible with Shannon, Popper, Fisher, and Zadeh's thoughts   ICFIE 2018, AISC 872 proceedings.
2017 EM算法是炼金术吗?   博客文章      

更早的关于语义信息论文章

CM算法示范文件包 The pakage of Demo files for Maximum mutual infrmation classifications and Mixture models

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Papers on ArXiv

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Ealier papers about information, information value, and philosophy