aboutsummaryrefslogtreecommitdiff
diff options
context:
space:
mode:
-rw-r--r--posts/2019-02-14-raise-your-elbo.md2
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