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| -rw-r--r-- | posts/2019-02-14-raise-your-elbo.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/posts/2019-02-14-raise-your-elbo.md b/posts/2019-02-14-raise-your-elbo.md index 5d4c2dd..e6d8c18 100644 --- a/posts/2019-02-14-raise-your-elbo.md +++ b/posts/2019-02-14-raise-your-elbo.md @@ -172,7 +172,7 @@ $$\begin{aligned} &= \text{argmax}_\theta \sum_i \mathbb E_{p(z_{i} | x_{i}; \theta_t)} \log p(x_{i}, z_{i}; \theta) \qquad (2.3) \end{aligned}$$ -So $\sum_i L(p(x_{i}, z_{i}; \theta), q(z_i)$ is non-decreasing at both the +So $\sum_i L(p(x_{i}, z_{i}; \theta), q(z_i))$ is non-decreasing at both the E-step and the M-step. We can see from this derivation that EM is half-Bayesian. The E-step is |