--- a/writeup/nips2010_submission.tex	Wed Jun 02 13:09:27 2010 -0400
+++ b/writeup/nips2010_submission.tex	Wed Jun 02 13:30:35 2010 -0400
@@ -536,7 +536,7 @@
 \centerline{\resizebox{.99\textwidth}{!}{\includegraphics{images/error_rates_charts.pdf}}}
 \caption{SDAx are the {\bf deep} models. Error bars indicate a 95\% confidence interval. 0 indicates that the model was trained
 on NIST, 1 on NISTP, and 2 on P07. Left: overall results
-of all models, on 3 different test sets (NIST, NISTP, P07).
+of all models, on NIST and NISTP test sets.
 Right: error rates on NIST test digits only, along with the previous results from 
 literature~\citep{Granger+al-2007,Cortes+al-2000,Oliveira+al-2002-short,Milgram+al-2005}
 respectively based on ART, nearest neighbors, MLPs, and SVMs.}
@@ -594,7 +594,7 @@
 NIST test set error brought by the use of out-of-distribution examples
 (i.e. the perturbed examples examples from NISTP or P07). 
 Relative percent change is measured by taking
-100 \% \times (original model's error / perturbed-data model's error - 1).
+$100 \% \times$ (original model's error / perturbed-data model's error - 1).
 The right side of
 Figure~\ref{fig:improvements-charts} shows the relative improvement
 brought by the use of a multi-task setting, in which the same model is
@@ -605,7 +605,7 @@
 for the SDA.  Note that to simplify these multi-task experiments, only the original
 NIST dataset is used. For example, the MLP-digits bar shows the relative
 percent improvement in MLP error rate on the NIST digits test set 
-is 100\% $\times$ (1 - single-task
+is $100\% \times$ (1 - single-task
 model's error / multi-task model's error).  The single-task model is
 trained with only 10 outputs (one per digit), seeing only digit examples,
 whereas the multi-task model is trained with 62 outputs, with all 62