
Understanding and Accelerating EM Algorithm's Convergence by Fair Competition Principle and RateVerisimilitude Function
Why can the ExpectationMaximization (EM) algorithm for mixture models c...
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Fair Marriage Principle and Initialization Map for the EM Algorithm
The popular convergence theory of the EM algorithm explains that the obs...
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Channels' Confirmation and Predictions' Confirmation: from the Medical Test to the Raven Paradox
After long arguments between positivism and falsificationism, the verifi...
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The CM Algorithm for the Maximum Mutual Information Classifications of Unseen Instances
The Maximum Mutual Information (MMI) criterion is different from the Lea...
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From the EM Algorithm to the CMEM Algorithm for Global Convergence of Mixture Models
The ExpectationMaximization (EM) algorithm for mixture models often res...
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From Bayesian Inference to Logical Bayesian Inference: A New Mathematical Frame for Semantic Communication and Machine Learning
Bayesian Inference (BI) uses the Bayes' posterior whereas Logical Bayesi...
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Semantic Channel and Shannon's Channel Mutually Match for MultiLabel Classification
A group of transition probability functions form a Shannon's channel whe...
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From Shannon's Channel to Semantic Channel via New Bayes' Formulas for Machine Learning
A group of transition probability functions form a Shannon's channel whe...
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Illustrating Color Evolution and Color Blindness by the Decoding Model of Color Vision
A symmetrical model of color vision, the decoding model as a new version...
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Chenguang Lu
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