post dec20 fix4

_posts/2023-1-20-The_Heilmeier_Catechism.md

@@ -8,7 +8,7 @@ title: The Heilmeier Catechism
 - George H. Heilmeier, a former DARPA director (1975-1977), crafted a set of questions known as the **Heilmeier Catechism** 
 to help Agency officials think through and evaluate proposed research programs.
 
-> ### The 8 Questions
+### The 8 Questions
 
     1. What are you trying to do? Articulate your objectives using absolutely no jargon.
 

_posts/2023-12-20-TIL_Dec_20.md

@@ -1,20 +1,18 @@
 ---
 layout: post
-title: TIL(20/12/23) 
+title: TIL (20/12/23) 
 ---
 
 ## Bayesian Optimization
 
 **Bayesian optimization** is a powerful strategy for finding the extrema of objective functions that are expensive to evaluate. It is particularly useful when these evaluations are costly, when one does not have access to derivatives, or when the problem at hand is non-convex. 
 
-```
  The Bayesian Optimization algorithm can be summarized as follows:
 
     1. Select a Sample by Optimizing the Acquisition Function.
     2. Evaluate the Sample With the Objective Function.
     3. Update the Data and, in turn, the Surrogate Function.
     4. Go To 1.
-```
 
 - It uses a 
     - **Surrogate function** - that approximates the relationship between I/O data of the sample. There are many ways to model, one of the ways is to use Random Forest/Gaussian Process (GP, with many different kernels) i.e here we're kind of approximating the *objective function* such that it can be *easily sampled*.