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Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.
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Variational Inference
This answer may start a bit too far 'at the beginning', but you can see from which point onwards I start talking about things that are new to you.
In Bayesian statistics $\mu_n$ and $\tau_k$ are cal …
1
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1
answer
154
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Sampling from conditional posterior - continuous and discrete terms
I'm working through Hierarchically Supervised LDA by Perotte et all (2011). The conditional posterior I'm supposed to sample values $z_i$ from, however, is zero almost everywhere.
To see why, lets h …
4
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1
answer
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Gibbs sampling in Hierarchically Supervised LDA (HSLDA)
TL;DR
In the HSLDA paper by Perotte et al, the posterior conditional distribution of $z_{d,n}$ for Gibbs Sampling is specified as:
\begin{equation*}
p(z_{d,n}=k| \mathbf{z}_{-d,n}, \mathbf{a}, \math …