Update README.md

README.md

@@ -1,19 +1,20 @@
 # HyperparameterSteepness
 
-Very often in machine learning, one needs to control a hyperparameter value such as the learning rate over the epochs. A specific example would consist of an exponential decay of a learning rate eta over the epochs. However, the optimal shape of such a controlling curve is not known. Either a fast decay, linear decay or even a slow-start decay are needed. Similar to the gamma parameter in image-intensity adjustment, a single parameter, here alpha, can control the convexity of the hyperparameter curve over epochs. We have used the trick in training of Kohohen maps and in controlling the leniency of a reward schedule in reinforcement learning (see below).
+Very often in machine learning, one needs to control a hyperparameter value such as the learning rate over the epochs. A specific example would consist of an exponential decay of a learning rate eta over the epochs. However, the optimal shape of such a controlling curve is not known. Either a fast decay, linear decay or even a slow-start decay may be needed. Similar to the gamma parameter in image-intensity adjustment, a single parameter, here alpha, can control the convexity of the hyperparameter curve over epochs. We have used the trick in training of Kohohen maps and in controlling the leniency of a reward schedule in reinforcement learning (see below).
 
 ![Screenshot](steepness-curves.png)
 
-Enclosed is the steepness .c program with a bash script and .png graph for several steepness (alpha) values. As an example, the tolerance runs from 0.4 in the beginning to 0.01 at the end.  
+Enclosed is the steepness .c program with a bash script and .png graph for several steepness (alpha) values. As an example, the hyperparameter value runs from 0.4 in the beginning to 0.01 at the end of a series of training epochs.
 
 You can make the binary by gcc steepness.c -lm -o steepness 
 
 To run the demo script you need to install gnuplot 
 The *.curves file and .png are already made and present in the package.  
 
-You can cite Schomaker & Bulacu (2004), Eq. 8.  Schomaker, L & Bulacu, M 2004, 'Automatic writer identification using connected-component contours and edge-based features of uppercase western script', Ieee transactions on pattern analysis and machine intelligence, vol. 26, no. 6, pp. 787-798.  
+You can cite Schomaker & Bulacu (2004), Eq. 8.  Schomaker, L & Bulacu, M 2004, 'Automatic writer identification using connected-component contours and edge-based features of uppercase western script', IEEE transactions on pattern analysis and machine intelligence, vol. 26, no. 6, pp. 787-798.  
 
 The function is also used in the following publication: 
+```
 @article{Luo_2020, 
   title={Accelerating Reinforcement Learning for Reaching Using Continuous Curriculum Learning}, 
   ISBN={9781728169262}, url={http://dx.doi.org/10.1109/IJCNN48605.2020.9207427}, 
@@ -23,3 +24,4 @@ The function is also used in the following publication:
   author={Luo, Sha and Kasaei, Hamidreza and Schomaker, Lambert}, 
   year={2020}, month={Jul} 
 }
+```