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Here , we leverage a logistic stick-breaking representation and recent innovations in Pólya-gamma augmentation to reformu-late the multinomial distribution in terms of latent variables with jointly Gaussian likelihoods , enabling us to take advantage of a host of Bayesian inference techniques for Gaussian models with minimal overhead .
 used for: logistic stick-breaking representation, multinomial distribution; used for: Pólya-gamma augmentation, multinomial distribution; part of: latent variables, multinomial distribution; feature of: jointly Gaussian likelihoods, latent variables; used for: Bayesian inference techniques, Gaussian models; feature of: minimal overhead, Gaussian models
Given a phrase that describes the relationship between two words, extract the words and the lexical relationship between them. The output format should be "relation1: word1, word2; relation2: word3, word4". 
Option: conjunction, feature of, hyponym of, used for, part of, compare, evaluate for 
Text: {0} 
Answer:
 used for: logistic stick-breaking representation, multinomial distribution; used for: Pólya-gamma augmentation, multinomial distribution; part of: latent variables, multinomial distribution; feature of: jointly Gaussian likelihoods, latent variables; used for: Bayesian inference techniques, Gaussian models; feature of: minimal overhead, Gaussian models