From d9510470cd3242471fe1146353b4eba144089aec Mon Sep 17 00:00:00 2001
From: Dane Sabo <dane.sabo@pitt.edu>
Date: Tue, 1 Apr 2025 13:01:58 -0400
Subject: [PATCH] vault backup: 2025-04-01 13:01:58

---
 .sessions/Thesis_Notes.vim                    | 14 ++++++++------
 ...mal Methods applied to Machine Learning.md | 19 +++++++++++++++++++
 2 files changed, 27 insertions(+), 6 deletions(-)

diff --git a/.sessions/Thesis_Notes.vim b/.sessions/Thesis_Notes.vim
index 816f8ef2..1c3dd603 100644
--- a/.sessions/Thesis_Notes.vim
+++ b/.sessions/Thesis_Notes.vim
@@ -3,7 +3,7 @@ let s:so_save = &g:so | let s:siso_save = &g:siso | setg so=0 siso=0 | setl so=-
 let v:this_session=expand("<sfile>:p")
 silent only
 silent tabonly
-cd ~/Documents/Dane\'s\ Vault/9999\ Personal/Journal
+cd ~/Documents/Dane\'s\ Vault/5\ Thesis
 if expand('%') == '' && !&modified && line('$') <= 1 && getline(1) == ''
   let s:wipebuf = bufnr('%')
 endif
@@ -13,11 +13,13 @@ if &shortmess =~ 'A'
 else
   set shortmess=aoO
 endif
-badd +16 ~/Documents/Dane\'s\ Vault/5\ Thesis/4\ Meetings/DGC_DAS_328.md
+badd +16 4\ Meetings/DGC_DAS_328.md
+badd +32 5\ Resources/Literature_Reviews/A\ Review\ of\ Formal\ Methods\ applied\ to\ Machine\ Learning.md
 argglobal
 %argdel
-edit ~/Documents/Dane\'s\ Vault/5\ Thesis/4\ Meetings/DGC_DAS_328.md
+edit 5\ Resources/Literature_Reviews/A\ Review\ of\ Formal\ Methods\ applied\ to\ Machine\ Learning.md
 argglobal
+balt 4\ Meetings/DGC_DAS_328.md
 setlocal fdm=manual
 setlocal fde=0
 setlocal fmr={{{,}}}
@@ -28,12 +30,12 @@ setlocal fdn=20
 setlocal fen
 silent! normal! zE
 let &fdl = &fdl
-let s:l = 16 - ((15 * winheight(0) + 30) / 60)
+let s:l = 11 - ((10 * winheight(0) + 27) / 55)
 if s:l < 1 | let s:l = 1 | endif
 keepjumps exe s:l
 normal! zt
-keepjumps 16
-normal! 080|
+keepjumps 11
+normal! 058|
 tabnext 1
 if exists('s:wipebuf') && len(win_findbuf(s:wipebuf)) == 0 && getbufvar(s:wipebuf, '&buftype') isnot# 'terminal'
   silent exe 'bwipe ' . s:wipebuf
diff --git a/5 Thesis/5 Resources/Literature_Reviews/A Review of Formal Methods applied to Machine Learning.md b/5 Thesis/5 Resources/Literature_Reviews/A Review of Formal Methods applied to Machine Learning.md
index 06582d1d..59445856 100644
--- a/5 Thesis/5 Resources/Literature_Reviews/A Review of Formal Methods applied to Machine Learning.md	
+++ b/5 Thesis/5 Resources/Literature_Reviews/A Review of Formal Methods applied to Machine Learning.md	
@@ -11,4 +11,23 @@ This review seems to talk a good bit about that.
 than other types of programming. Things such as computer vision and decision
 making are very difficult to program manually relative to their ML counterpart.
 
+- Abstract interpretation can connect different formal methods that otherwise
+would seem disjoint, according to these authors.
+
+- They spend a lot of pages (~15) on *formal methods for neural networks*. 
+There are two kinds.
+
+    - **Complete Formal Methods** are sound and complete, and can provide 
+    counterexamples where appropriate. That being said, they are not usually 
+    sound on floating point arithmetic and often neglect rounding errors.
+
+    - **Incomplete Formal Methods** are generally able to scale to larger 
+    neural networks, and are often sound, but generally suffer from false 
+    positives.
+
+- In comparison, they spend 2 pages on support vector machines and decision
+trees :( What did they ever do to you man!
+
+- They also mention that formal methods for data preparation and training are
+very much works in progress.