Reorder release notes

Author: twiecki

RELEASE-NOTES.md

@@ -6,8 +6,22 @@
 
 * [Add Gaussian Process submodule](http://pymc-devs.github.io/pymc3/notebooks/GP-introduction.html)
 
+* Much improved variational inference support:
+
+  - [Add Operator Variational Inference (experimental).](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html)
+
+  - [Add Stein-Variational Gradient Descent as well as Amortized SVGD (experimental).](https://github.com/pymc-devs/pymc3/pull/2183)
+
+  - [Add pm.Minibatch() to easily specify mini-batches.](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html#Minibatch-ADVI)
+
+  - Added various optimizers including ADAM.
+  
+  - Stopping criterion implemented via callbacks.
+
 * sample() defaults changed: tuning is enabled for the first 500 samples which are then discarded from the trace as burn-in.
 
+* MvNormal supports Cholesky Decomposition now for increased speed and numerical stability.
+
 * Many optimizations and speed-ups.
 
 * NUTS implementation now matches current Stan implementation.
@@ -18,24 +32,10 @@
 
 * [Add live-trace to see samples in real-time.](http://pymc-devs.github.io/pymc3/notebooks/live_sample_plots.html)
 
-* ADVI stopping criterion implemented.
-
 * Improved support for theano's floatX setting to enable GPU computations (work in progress).
 
-* MvNormal supports Cholesky Decomposition now for increased speed and numerical stability.
-
 * [Add Elliptical Slice Sampler.](http://pymc-devs.github.io/pymc3/notebooks/GP-slice-sampling.html)
 
-* Much improved variational inference support:
-
-  - [Add Operator Variational Inference (experimental).](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html)
-
-  - [Add Stein-Variational Gradient Descent as well as Amortized SVGD (experimental).](https://github.com/pymc-devs/pymc3/pull/2183)
-
-  - [Add pm.generator() to easily specify mini-batches.](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html#Minibatch-ADVI)
-
-  - Added various optimizers including ADAM.
-
 * [Sampled posteriors can now be turned into priors for Bayesian updating with a new interpolated distribution.](https://github.com/pymc-devs/pymc3/pull/2163)
 
 * `Model` can now be inherited from and act as a base class for user specified models (see pymc3.models.linear).
@@ -44,8 +44,6 @@
 
 * GLM models do not need a left-hand variable anymore.
 
-* Add support for cholesky parametrizations for cov/corr matrices.
-
 * Refactored HMC and NUTS for better readability.
 
 * Add support for Python 3.6.