Difference between r1.128 and the current
@@ -441,7 +441,7 @@
=== ring counter ===
curr at [[원핫%2Cone-hot?action=highlight&value=counter]]
[#countable]
countability n.
curr at [[원핫%2Cone-hot?action=highlight&value=counter]]
[#countable]
== countability #countable =
== countability #countable ==
countable adj.countability n.
@@ -485,20 +485,22 @@
[#allocator]
Ggl:"memory allocator"
Bing:"memory allocator"
"memory allocator"
'''memory allocator'''
메모리할당자
메모리할당기
중에?
w l
https://en.wiktionary.org/wiki/memory_allocator x 2024-06
// memory allocator .... Ggl:"memory allocator" Bing:"memory allocator" NN:"memory allocator"
Srch:memory_allocatorUp: allocator( [할당자,allocator] or [할당기,allocator] or 얼로케이터 )
[[slab_allocator]] =,slab_allocator . slab_allocator
[[WtEn:slab_allocator]]
@@ -645,33 +647,65 @@
[#sort]
= sort / sorting / 정렬 #sort =
(대충 생각나는대로,chk) { [[키,key]]를 기준으로(primary_key 말고 secondary_key ...도 있는 경우가 있는데 tbw) , [[비교,comparison]]하여, (근데 Ggl:"비교정렬" 이 아닌 경우도 있는데 tbw) [[순서,order]]에 따라, 위치를 바꾸어서(교환, swap, exchange) }
Sub:
radix
[[radix_sort]] ... curr at [[래딕스,radix?action=highlight&value=radix_sort]]
merge
comb
https://everything2.com/title/comb+sort
spaghetti
comb
shear
zen
https://everything2.com/title/Zen+Sort
random / bogo / stupid /
https://everything2.com/title/random+sort
== algorithm ==
== stable vs unstable ==
https://everything2.com/title/stable+sort
= sort / sorting / 정렬 #sort =
(대충 생각나는대로,chk) { [[키,key]]를 기준으로(primary_key 말고 secondary_key ...도 있는 경우가 있는데 tbw) , [[비교,comparison]]하여, (근데 Ggl:"비교정렬" 이 아닌 경우도 있는데 tbw) [[순서,order]]에 따라, 위치를 바꾸어서(교환, swap, exchange) }
=정렬,sorting =,sorting =,sort .
[[정렬,jeongryeol]] =정렬,sorting =,sorting =,sort .
sort WtEn:sort#Noun
sorting WtEn:sorting#Noun
소팅
Sub:
[[sort_명령]]
[[sort_명령]]?
----
정렬알고리즘을 분류하는 방법은 매우 다양한데
안정적인 정렬 vs 불안정 정렬
Naver:"안정적인 정렬 vs 불안정 정렬" Bing:"안정적인 정렬 vs 불안정 정렬" Ggl:"안정적인 정렬 vs 불안정 정렬"
안정:
불안정: quicksort
정렬알고리듬의 분류와 밀접:
[[시간복잡도,time_complexity]] <- 특히 가장 중요 주제.
[[공간복잡도,space_complexity]] - 일부에서.
----
radix
[[radix_sort]] ... curr at [[래딕스,radix?action=highlight&value=radix_sort]]
'''radix sort'''
Ggl:"radix sort"
merge
'''merge sort'''
https://everything2.com/title/Merge+SortGgl:"merge sort"
comb
https://everything2.com/title/comb+sort
Ggl:"comb sort"
spaghetti
Ggl:"spaghetti sort"
shear
Ggl:"shear sort"
quick - quicksort quick_sort
quick
quicksort quick_sort =,quicksort =,quick_sort ... WtEn:quicksort
Ggl:"quick sort"
REL
[[pivot]] - [[피벗,pivot]]
불안정정렬
[[시간복잡도,time_complexity]] \Theta(n\log n) O(n^2)
zen
https://everything2.com/title/Zen+Sort
Ggl:"zen sort"
random / bogo / stupid /
https://everything2.com/title/random+sort
Ggl:"random bogo stupid sort"
== stable vs unstable ==
https://everything2.com/title/stable+sort
@@ -1412,3 +1446,98 @@
[[오에스2,OS2]]?
일단 입출력은 [[입출력,IO]]로 했는데 ,,편의상,,
일단 입출력은 [[입출력,IO]]로 했는데 ,,편의상,,
= tmp 1 =
tmp/ written by dr j. lee, https://cafe.naver.com/kpope/931
[[라그랑지안,Lagrangian]]은 먼저 $F=ma$ 에서 바로 나옵니다.
$F=-\nabla U$ 이고 $ma=m\ddot{x}=\frac{d}{dt} [m\dot{x}]$ 입니다.
그런데 $m\dot{x}=\frac{\partial}{\partial \dot{x}} \frac{1}{2}m\dot{x}^2$
이므로 $m\dot{x}=\frac{\partial}{\partial \dot{x}} T$ 입니다.
Cartesian coordinate에서는 kinetic energy T가 오직 $\dot{x}$ dependent
potential energy $V$ 가 오직 $x$ dependent (물론 velocity independent potential 에서)(
그러니
$F=ma$ 는 Euler-Lagrange equation과 equivalent합니다.
$\left[ \frac{\partial}{\partial x}-\frac{d}{dt}\frac{\partial}{\partial\dot{x}}\right](T-V)$
문제는 이것이 least-action principle로부터 유도되는 이유가 key입니다.
당시 Euler는 brachistochrone 문제들을 통해 이미 최소값과 관련한 calculus of variation 을 개발해 놓았고
이것이 이렇게 응용되어 결국 Hamilton's least-action principle로 완성되게 됩니다.
= tmp2 =
2024-06-06
Prof. Michael Bronstein (CS, University of Oxford, DeepMind prof. -> https://www.cs.ox.ac.uk/news/1996-full.html ) delivered a lecture titled
''Geometric Deep Learning: From Euclid to Drug Design''
as part of the Hot Topics in Computing Series at CSAIL.
https://www.youtube.com/watch?v=MeJgxYfiaz8
1:07
He's very well known for dynamic graph CNNs for learning on point clouds. // [[dynamic_graph_CNN]] [[점구름,point_cloud]]
3:30
[[Hermann_Weyl]]: "Symmetry, as wide or as narrow as you may define its meaning, is one idea by which man through the ages has tried to comprehend and create order, beauty, and perfection" // [[대칭성,symmetry]]
4:00
[[플라톤,Plato]] (~370 BC)의 [[Platonic_solid]] (플라톤 입체 or 플라톤 다면체 ... [[입체,solid]]) 언급
4:44
[[에우클레이데스,Euclid]] (~300 BC)의 5th postulate, and 19세기에 나타난 비유클리드 언급
entire zoo of different geometries
* Euclidean
* affine
* projective
Euclidean_geometry [[유클리드_기하학,Euclidean_geometry]]
affine_geometry [[아핀기하학,affine_geometry]]
projective_geometry [[사영기하학,projective_geometry]]
이런 상황에서 '기하학을 어떻게 정의할 것인가'의 문제가 제기. (어떤 기하학이 다른 것보다 일반적인가?)
paradigm shift는 젊은 [[Felix_Klein]] (1872) { 23세에 독일 Erlangen 대학교 교수. }로부터 왔는데
그는 radically new way of thinking of geometry in terms of invariances 를 제안하였다. // [[불변성,invariance]]
geometric object를 group of transformations // 기하학적 [[대상,object]]: [[군,group]] of [[변환,transformation]]
-> [[Erlangen_program]]. WpKo:에를랑겐_프로그램 WpEn:Erlangen_program {Topics: [[동차공간,homogeneous_space]] }
6:00
ex.
Euclidean geometry
E(3)
https://i.imgur.com/TAZCDGI.png
[[Emmy_Noether]]: [[뇌터_정리,Noether_theorem]]: principles of symmetry에서 [[보존법칙,conservation_law]]을 도출할 수 있음을 보였음.
like: conservation of energy comes from symmetry of time.
([[에너지,energy]] 보존은 [[시간,time]] 대칭에서)
이것이 나중에 발전하여 [[입자물리학,particle_physics]]의 [[standard_model]].
6:56
물리에선 external vs internal symmetry를 구분
external symmetries of the spacetime - what is called the [[푸앵카레_군,Poincare_group]], that gives rise to the [[
external symmetry - R^^1,3^^ O(1,3) ...
internal symmetry - U(1) SU(2) SU(3) ...
7:30
"It is only slightly overstating the case to say that Physics is the study of symmetry" - P. Anderson // [[대칭성,symmetry]]
그럼 이게 ML([[기계학습,machine_learning]])과 무슨 관련인가?
We have historically different architectures of [[신경망,neural_network]]s such as
GNN
CNN
RNN
DeepSets
[[트랜스포머,transformer]]
...
다른 context에서 온 다른 architecture이다.
우린 여기서 [[공통분모,common_denominator]]를 찾고 싶다. (이미 있던 것들을) 설명하고, 같은 원리에 기반해 새로운 architecture를 설계(design)하는 걸 하고 싶은데, 이게 바로 GNN이다.
cont 8m
= allocator #allocator =
[[할당자,allocator]] ? [[할당,allocation]]하는
=할당자,allocator =,allocator =,allocator . allocator
~~WtEn:allocator = https://en.wiktionary.org/wiki/allocator (볼필요x easy)~~
Bing:allocator
allocator
Srch:allocator
Contents
- 1. 메타 meta #meta
- 2. infinitive #infinitive 부정사 ?
- 3. geometry 기하 #geom
- 3.1. taxicab???
- 3.2. digital geometry
- 3.3. discrete geometry and combinatorial geometry
- 3.4. computational geometry
- 3.5. finite geometry
- 3.6. descriptive geometry
- 3.7. projective geometry
- 3.8. Euclidean geometry #euclidgeom
- 3.9. non-Euclidean geometry
- 3.10. absolute geometry
- 3.11. hyperbolic geometry
- 3.12. affine geometry
- 3.13. // rel. parallel_postulate
- 3.14. 리만 기하학
- 3.15. 정보기하학 information geometry
- 4. lock / locking
- 5. envelope
- 6. count / counting / counter + countability #count
- 7. 암호학 cryptology cryptography
- 8. context
- 9. expansion
- 10. transfer #transfer
- 11. generator #generator
- 12. sort / sorting / 정렬 #sort
- 13. fork / forking #fork
- 14. branch / branching #branch
- 15. (tmp, 위 두 sections.) fork vs branch
- 16. vertex #vertex
- 17. edge #edge
- 18. ambiguity
- 19. law / rule /
- 20. dual / duality
- 21. (시간 관련) past - (present) - future / priori posteriori / a priori a posteriori
- 22. 분해 decomposition
- 23. statistics
- 24. prediction / forecasting
- 25. meaning
- 26. closure #closure
- 27. 동기화,synchronization
- 28. denotation and connotation
- 29. natural language
- 30. 처리 processing
- 31. NLP
- 32. hidden Markov model HMM
- 33. Markov model
- 34. Intel_x86
- 35. disk
- 36. cone
- 37. mimetex version
- 38. referer test
- 39. gnuplot test
- 40. etc
- 41. TeX의 그리스 문자
- 42. orphaned pages
- 43. 이상익
- 44. Pagename Normalization
- 45. tmp 1
- 46. tmp2
- 47. allocator #allocator
1. 메타 meta #meta ¶
Sub:
metadata - 메타데이터,metadata or 메타자료,metadata .... metadata metadata
{
metaprogramming
메타프로그래밍
metadata - 메타데이터,metadata or 메타자료,metadata .... metadata metadata
p TheMetadata
metaobject metaobject =,metaobject . metaobject{
metaobject
객체,object or 대상,object?
MKL metaobject_protocol(MOP)
metaobject
https://en.wikipedia.org/wiki/Metaobject
} // metaobject metaobject metaobject metaobject metaobject 메타오브젝트
메타프로그래밍,metaprogramming =메타프로그래밍,metaprogramming =,metaprogramming . 메타프로그래밍 metaprogramming - 프로그래밍,programmingmetaobject
객체,object or 대상,object?
MKL metaobject_protocol(MOP)
metaobject
https://en.wikipedia.org/wiki/Metaobject
} // metaobject metaobject metaobject metaobject metaobject 메타오브젝트
{
metaprogramming
메타프로그래밍
https://en.wikipedia.org/wiki/Metaprogramming
} // metaprogramming metaprogramming metaprogramming metaprogramming 메타프로그래밍 메타프로그래밍
메타이론,metatheory
메타정리,metatheorem
메타언어,metalanguage
{
} // metaprogramming metaprogramming metaprogramming metaprogramming 메타프로그래밍 메타프로그래밍
메타이론,metatheory
메타정리,metatheorem
메타언어,metalanguage
{
see also 논리학,logic#s-1.1
wk:
(Recall: 일단 '언어'는 '대상을 서술하는 것')
메타언어는 언어 그 자체를 서술/언급하는 언어나 심벌,symbol(기호,symbol).
고차언어라고도 한다. higher-order language ? higher-order language = metalanguage ?
'대상언어'가 있을 때 그 위에 그걸 서술하는 '메타언어'가 있는 것이다. (그래서 위에 aka high-order라고 한 것? chk)
(Recall: 일단 '언어'는 '대상을 서술하는 것')
메타언어는 언어 그 자체를 서술/언급하는 언어나 심벌,symbol(기호,symbol).
고차언어라고도 한다. higher-order language ? higher-order language = metalanguage ?
Are higher-order language and metalanguage the same?
Are higher-order language and metalanguage the same?
메타언어의 문장,sentence이나 절,clause의 구조는 메타문법( 메타문법 메타문법 metasyntax ? metagrammar ? ) 으로 기술,description된다.Are higher-order language and metalanguage the same?
'대상언어'가 있을 때 그 위에 그걸 서술하는 '메타언어'가 있는 것이다. (그래서 위에 aka high-order라고 한 것? chk)
https://ko.wikipedia.org/wiki/메타_언어
} // metalanguage
메타수학,metamathematics =메타수학,metamathematics =,metamathematics 메타수학 metamathematics
{
https://ko.wikipedia.org/wiki/메타수학
https://en.wikipedia.org/wiki/Metamathematics
https://ja.wikipedia.org/wiki/超数学
} // metalanguage
메타수학,metamathematics =메타수학,metamathematics =,metamathematics 메타수학 metamathematics
{
https://ko.wikipedia.org/wiki/메타수학
https://en.wikipedia.org/wiki/Metamathematics
https://ja.wikipedia.org/wiki/超数学
...
메타수학
} // metamathematics
metagraph 메타그래프,graph ? - 그래프,graph?
metaclass 메타클래스,metaclass? - 클래스,class - curr at 클래스%2Cclass?action=highlight&value=meta#s-2.3
metasyntax - 다른 syntax를 기술,description하기 위한 syntax였나? chk - curr at 신택스,syntax?action=highlight&value=metasyntax
metasyntactic_variable - 이게 이름이 foo bar 그런거였는데... metasyntax와 비슷한, 이런 이름이 붙은 이유? 다른 프로그램(실질적으로 쓰일 어떤 프로그램)의 코드의 예시를 보여주기 위해, 즉 template? 실질적으로는 의미가 없는 그런 variable
metalogic =,metalogic =,metalogic . metalogic
{
metalogic
메타논리
메타논리학
중에?
메타수학
} // metamathematics
metagraph 메타그래프,graph ? - 그래프,graph?
metaclass 메타클래스,metaclass? - 클래스,class - curr at 클래스%2Cclass?action=highlight&value=meta#s-2.3
metasyntax - 다른 syntax를 기술,description하기 위한 syntax였나? chk - curr at 신택스,syntax?action=highlight&value=metasyntax
metasyntactic_variable - 이게 이름이 foo bar 그런거였는데... metasyntax와 비슷한, 이런 이름이 붙은 이유? 다른 프로그램(실질적으로 쓰일 어떤 프로그램)의 코드의 예시를 보여주기 위해, 즉 template? 실질적으로는 의미가 없는 그런 variable
metalogic =,metalogic =,metalogic . metalogic
{
metalogic
메타논리
메타논리학
중에?
rel formation_rule =,formation_rule =,formation_rule . formation_rule { formation rule formation_rule Formation_rule = https://en.wikipedia.org/wiki/Formation_rule ... "formation rule formation rule formation rule }
https://ko.wikipedia.org/wiki/메타논리학
https://simple.wikipedia.org/wiki/Metalogic
https://en.wikipedia.org/wiki/Metalogic
https://ja.wikipedia.org/wiki/メタ論理学
https://simple.wikipedia.org/wiki/Metalogic
https://en.wikipedia.org/wiki/Metalogic
https://ja.wikipedia.org/wiki/メタ論理学
Sub:
metalogic_programming =,metalogic_programming =,metalogic_programming . metalogic_programming
}
metalogic_programming =,metalogic_programming =,metalogic_programming . metalogic_programming
}
2.1. infinitive form 부정형 ? ¶
infinitive form
infinitive_form =,infinitive_form . infinitive_form
"infinitive form"
infinitive form infinitive form infinitive form
infinitive_form =,infinitive_form . infinitive_form
"infinitive form"
infinitive form infinitive form infinitive form
2.2. infinitive verb ¶
infinitive verb
"infinitive verb"
infinitive_verb =,infinitive_verb . infinitive_verb
infinitive_verb
infinitive_verb
"infinitive verb"
infinitive_verb =,infinitive_verb . infinitive_verb
infinitive_verb
infinitive_verb
3.1. taxicab??? ¶
taxicab_geometry =,taxicab_geometry =,taxicab_geometry . taxicab_geometry
{
taxicab geometry
(del or rename ok)
taxicab_geometry
MKL 거리,distance 노름,norm 그리드,grid 래티스,lattice 격자,lattice
taxicab geometry
taxicab geometry
"taxicab geometry"
}
{
taxicab geometry
(del or rename ok)
taxicab_geometry
MKL 거리,distance 노름,norm 그리드,grid 래티스,lattice 격자,lattice
taxicab geometry
taxicab geometry
"taxicab geometry"
}
3.2. digital geometry ¶
https://en.wikipedia.org/wiki/Digital_geometry
digital geometry
digital geometry
"digital geometry"
}
mentions
digital geometryhttps://en.wikipedia.org/wiki/Bresenham's_line_algorithm
digital_topology =,digital_topology =,digital_topology . digital_topology { digital_topology https://en.wikipedia.org/wiki/Digital_topology }
digital_manifold =,digital_manifold =,digital_manifold . digital_manifold { digital_manifold Digital_manifold = https://en.wikipedia.org/wiki/Digital_manifold }
digital_topology =,digital_topology =,digital_topology . digital_topology { digital_topology https://en.wikipedia.org/wiki/Digital_topology }
digital_manifold =,digital_manifold =,digital_manifold . digital_manifold { digital_manifold Digital_manifold = https://en.wikipedia.org/wiki/Digital_manifold }
digital geometry
digital geometry
"digital geometry"
}
3.3. discrete geometry and combinatorial geometry ¶
discrete_geometry =,discrete_geometry =,discrete_geometry . discrete_geometry
combinatorial_geometry =,combinatorial_geometry =,combinatorial_geometry . combinatorial_geometry
{
discrete geometry and combinatorial geometry
discrete geometry
combinatorial geometry
combinatorial_geometry =,combinatorial_geometry =,combinatorial_geometry . combinatorial_geometry
{
discrete geometry and combinatorial geometry
discrete geometry
combinatorial geometry
https://en.wikipedia.org/wiki/Discrete_geometry
"combinatorial geometry"
}
"Discrete geometry and combinatorial geometry are"
"discrete geometry""combinatorial geometry"
}
3.4. computational geometry ¶
computational geometry
computational_geometry =,computational_geometry =,computational_geometry . computational_geometry
{
computational geometry
계산기하
계산기하학
computational_geometry =,computational_geometry =,computational_geometry . computational_geometry
{
computational geometry
계산기하
계산기하학
https://ko.wikipedia.org/wiki/계산기하학
Computational_geometry = https://en.wikipedia.org/wiki/Computational_geometry
Computational_geometry = https://en.wikipedia.org/wiki/Computational_geometry
3.5. finite geometry ¶
finite geometry
finite_geometry =,finite_geometry =,finite_geometry . finite_geometry
finite_geometry
https://en.wikipedia.org/wiki/Finite_geometry
finite geometry
finite geometry
finite geometry
"finite geometry"
finite_geometry =,finite_geometry =,finite_geometry . finite_geometry
finite_geometry
https://en.wikipedia.org/wiki/Finite_geometry
finite geometry
finite geometry
finite geometry
"finite geometry"
finite_mathematics = discrete_mathematics 와 관계?? 근데 geometry에선 finite_geometry ≠ discrete_geometry ??
3.6. descriptive geometry ¶
descriptive_geometry =,descriptive_geometry =,descriptive_geometry . descriptive_geometry
{
descriptive geometry
descriptive_geometry
https://en.wikipedia.org/wiki/Descriptive_geometry
"descriptive geometry"
}
{
descriptive geometry
descriptive_geometry
https://en.wikipedia.org/wiki/Descriptive_geometry
"descriptive geometry"
}
기술
서술 ....??
서술 ....??
3.7. projective geometry ¶
projective_geometry =,projective_geometry =,projective_geometry . projective_geometry projective_geometry
{
projective geometry
projective geometry
projective_geometry
https://en.wikipedia.org/wiki/Projective_geometry
사영,projection
{
projective geometry
projective geometry
projective_geometry
https://en.wikipedia.org/wiki/Projective_geometry
사영,projection
3.8. Euclidean geometry #euclidgeom ¶
Euclidean_geometry =,Euclidean_geometry =,Euclidean_geometry . Euclidean_geometry
{
Euclidean geometry
Euclidean_geometry
https://ko.wikipedia.org/wiki/유클리드_기하학
https://en.wiktionary.org/wiki/Euclidean_geometry
Euclidean_geometry = https://en.wikipedia.org/wiki/Euclidean_geometry
유클리드 기하학 = https://namu.wiki/w/유클리드 기하학
{
Euclidean geometry
Euclidean_geometry
https://ko.wikipedia.org/wiki/유클리드_기하학
https://en.wiktionary.org/wiki/Euclidean_geometry
Euclidean_geometry = https://en.wikipedia.org/wiki/Euclidean_geometry
유클리드 기하학 = https://namu.wiki/w/유클리드 기하학
"Euclidean geometry"
Euclidean geometry
Euclidean geometry
"Euclidean geometry"
"Euclidean geometry"
}
Euclidean geometry
Euclidean geometry
"Euclidean geometry"
"Euclidean geometry"
}
3.9. non-Euclidean geometry ¶
non-Euclidean_geometry =,non-Euclidean_geometry =,non-Euclidean_geometry . non-Euclidean_geometry
{
비유클리드_기하학
non-Euclidean geometry
noneuclidean_geometry =,noneuclidean_geometry // https://en.wiktionary.org/wiki/noneuclidean_geometry <- US spelling
https://en.wiktionary.org/wiki/non-Euclidean_geometry
https://ko.wikipedia.org/wiki/비유클리드_기하학
https://simple.wikipedia.org/wiki/Non-Euclidean_geometry
https://en.wikipedia.org/wiki/Non-Euclidean_geometry
{
비유클리드_기하학
non-Euclidean geometry
noneuclidean_geometry =,noneuclidean_geometry // https://en.wiktionary.org/wiki/noneuclidean_geometry <- US spelling
https://en.wiktionary.org/wiki/non-Euclidean_geometry
https://ko.wikipedia.org/wiki/비유클리드_기하학
https://simple.wikipedia.org/wiki/Non-Euclidean_geometry
https://en.wikipedia.org/wiki/Non-Euclidean_geometry
}
쌍곡기하학 hyperbolic geometry hyperbolic_geometry hyperbolic_geometry ..... hyperbolic_space ? hyperbolic_space
타원기하학 elliptic geometry elliptic_geometry (aka elliptical_geometry ? chk) .... 타원 기하학이 적용되는 위상공간: 타원 공간(elliptic space) elliptic_space elliptic_space
타원기하학 elliptic geometry elliptic_geometry (aka elliptical_geometry ? chk) .... 타원 기하학이 적용되는 위상공간: 타원 공간(elliptic space) elliptic_space elliptic_space
3.10. absolute geometry ¶
절대기하,absolute_geometry =,absolute_geometry . absolute_geometry
{
absolute geometry
absolute_geometry
https://ko.wikipedia.org/wiki/절대기하학
https://en.wikipedia.org/wiki/Absolute_geometry
"absolute geometry"
}
{
absolute geometry
absolute_geometry
https://ko.wikipedia.org/wiki/절대기하학
https://en.wikipedia.org/wiki/Absolute_geometry
"absolute geometry"
}
3.11. hyperbolic geometry ¶
hyperbolic_geometry =,hyperbolic_geometry =,hyperbolic_geometry . hyperbolic_geometry
{
hyperbolic geometry
쌍곡기하
hyperbolic_geometry
https://ko.wikipedia.org/wiki/쌍곡기하학
https://simple.wikipedia.org/wiki/Hyperbolic_geometry
https://en.wikipedia.org/wiki/Hyperbolic_geometry
hyperbolic geometry
hyperbolic geometry
"hyperbolic geometry"
"hyperbolic geometry"
"hyperbolic geometry"
"hyperbolic geometry"
}
{
hyperbolic geometry
쌍곡기하
hyperbolic_geometry
https://ko.wikipedia.org/wiki/쌍곡기하학
https://simple.wikipedia.org/wiki/Hyperbolic_geometry
https://en.wikipedia.org/wiki/Hyperbolic_geometry
hyperbolic geometry
hyperbolic geometry
"hyperbolic geometry"
"hyperbolic geometry"
"hyperbolic geometry"
"hyperbolic geometry"
}
3.12. affine geometry ¶
affine_geometry =,affine_geometry =,affine_geometry . affine_geometry
{
affine geometry
https://mathworld.wolfram.com/AffineGeometry.html
https://en.wiktionary.org/wiki/affine_geometry
https://everything2.com/title/affine geometry
Affine_geometry = https://en.wikipedia.org/wiki/Affine_geometry
affine geometry
affine geometry
"affine geometry"
"affine geometry"
}
{
affine geometry
https://mathworld.wolfram.com/AffineGeometry.html
https://en.wiktionary.org/wiki/affine_geometry
https://everything2.com/title/affine geometry
Affine_geometry = https://en.wikipedia.org/wiki/Affine_geometry
affine geometry
affine geometry
"affine geometry"
"affine geometry"
}
3.14. 리만 기하학 ¶
리만 기하학(Riemannian geometry)
Riemannian geometry
Rel
리만_계량,Riemannian_metric =리만_계량,Riemannian_metric =,Riemannian_metric 리만_계량 Riemannian_metric { Riemannian metric "Riemannian metric" Riemannian metric }
리만_계량,Riemannian_metric =리만_계량,Riemannian_metric =,Riemannian_metric 리만_계량 Riemannian_metric { Riemannian metric "Riemannian metric" Riemannian metric }
Twin
"리만 기하학"
리만 기하학
리만 기하학
"Riemannian geometry"
Riemannian geometry
Riemannian geometry
Riemannian geometry
리만 기하학
리만 기하학
"Riemannian geometry"
Riemannian geometry
Riemannian geometry
Riemannian geometry
4. lock / locking ¶
Sub:
=,deadlock . deadlock
{
deadlock
http://wiki.c2.com/?DeadLock
}
=,livelock . livelock
{
livelock
http://wiki.c2.com/?LiveLock
=,deadlock . deadlock
{
deadlock
http://wiki.c2.com/?DeadLock
}
=,livelock . livelock
{
livelock
http://wiki.c2.com/?LiveLock
aka process_starvation ( Up: resource_starvation ? or just starvation ? )
}
lock-free_synchronization
lock-based_synchronization = pessimistic_locking
read write lock
http://wiki.c2.com/?ReadWriteLock
read write lock
}
lock-free_synchronization
lock-based_synchronization = pessimistic_locking
read write lock
http://wiki.c2.com/?ReadWriteLock
read write lock
6. count / counting / counter + countability #count ¶
count
counting
counter
countability
v. 세다
adj. 역- 반대- 의 뜻도 있음 - counter emf, ccw, etc.
countingadj. 역- 반대- 의 뜻도 있음 - counter emf, ccw, etc.
세기
counter세는 변수
세는 기계 - 계수기 ,
countability세는 기계 - 계수기 ,
가산성
countcounting
counter
countability
6.4. countability #countable ¶
countable adj.
countability n.
countability n.
Sub:
가산집합,countable_set =가산집합,countable_set =,countable_set 가산집합 countable_set (at local w)
countable_infinity - w
countable_additivity - w
가산공리 or 가산성공리 / countability_axiom or axiom_of_countability - w
가산집합,countable_set =가산집합,countable_set =,countable_set 가산집합 countable_set (at local w)
가산집합
셀수있는집합
countable_set
opp. 비가산집합,uncountable_set
countable set { countable set = 가산집합 = 셀수있는집합 VS. 셀수없는집합 = 비가산집합}
가산집합
countable_set
비가산집합,uncountable_set =비가산집합,uncountable_set 비가산집합,uncountable_set 비가산집합 uncountable_set셀수있는집합
countable_set
opp. 비가산집합,uncountable_set
countable set { countable set = 가산집합 = 셀수있는집합 VS. 셀수없는집합 = 비가산집합}
가산집합
countable_set
countable_infinity - w
countable_additivity - w
가산공리 or 가산성공리 / countability_axiom or axiom_of_countability - w
가산성,countability - w
6.5. memory allocator ¶
메모리할당자,memory_allocator ? 메모리,memory를 할당,allocation하는 i.e. 메모리할당,memory_allocation하는
memory allocator
메모리할당자
메모리할당기
중에?
memory allocator
메모리할당자
메모리할당기
중에?
w l
https://en.wiktionary.org/wiki/memory_allocator x 2024-06
// memory allocator .... memory allocator memory allocator memory allocator
memory_allocator
// memory allocator .... memory allocator memory allocator memory allocator
memory_allocator
6.5.1. slab allocator ¶
slab_allocator =,slab_allocator . slab_allocator
slab_allocator
https://www.minzkn.com/moniwiki/wiki.php/SlabAllocator
slab allocator
slab allocator
"slab allocator"
slab_allocator
slab_allocator
https://www.minzkn.com/moniwiki/wiki.php/SlabAllocator
slab allocator
slab allocator
"slab allocator"
slab_allocator
7. 암호학 cryptology cryptography ¶
=암호학, =,cryptology =,cryptography .
둘중에 pagename tbd
cryptology cryptography
암호학,cryptology
암호학,cryptography
cryptology cryptography 차이
cryptology cryptography 차이
cryptology cryptography 차이
둘중에 pagename tbd
둘다 page 만들어서 역할을 나눌수도
cryptology cryptographycryptology cryptography
암호학,cryptology
암호학,cryptography
cryptology cryptography 차이
cryptology cryptography 차이
cryptology cryptography 차이
Intw:
암호학
https://simple.wikipedia.org/wiki/Cryptography
http://en.citizendium.org/wiki/Cryptography
https://en.wikipedia.org/wiki/Cryptography
암호학
https://simple.wikipedia.org/wiki/Cryptography
http://en.citizendium.org/wiki/Cryptography
https://en.wikipedia.org/wiki/Cryptography
8. context ¶
Sub:
맥락,context
문맥,context
실행맥락,execution_context - context is curr at there too
context_switching
....
맥락,context
문맥,context
실행맥락,execution_context - context is curr at there too
context_switching
....
context_sensitivity ?
context sensitivity
https://en.wikipedia.org/wiki/Context-sensitive
이 개념은 언어,language 문법,grammar 자동기계,automaton = 유한상태기계(fsm)에 나온다
https://en.wikipedia.org/wiki/Context-sensitive
이 개념은 언어,language 문법,grammar 자동기계,automaton = 유한상태기계(fsm)에 나온다
9. expansion ¶
=,expansion .
expansion
expansion
expansion
수학에선 전개. vg에 현재 expansi로 보면 두개:
expansion
expansion
expansion
수학에선 전개. vg에 현재 expansi로 보면 두개:
이항전개,binomial_expansion
전개,expansion
페이지 있음전개,expansion
text_expansion text_expansion text expansion
brace_expansion brace_expansion Brace_expansion p BraceExpansion https://rosettacode.org/wiki/Brace_expansion brace expansion
rel. pattern_matching
11. generator #generator ¶
generator =,generator . generator
생성기 생성기,generator
생성자
제너레이터
발전기
발생기 - 난수발생기
RNG random number generator 등 ...
...
rel. generation { 생성,generation or 세대
생성기 생성기,generator
생성자
제너레이터
발전기
발생기 - 난수발생기
RNG random number generator 등 ...
...
rel. generation { 생성,generation or 세대
....(etc, misc)
VG titles with "genera" at 2023-08-20
생성모형,generative_model
생성함수,generating_function
확률생성함수,probability_generating_function,PGF
VG titles with "genera" at 2023-08-20
생성모형,generative_model
생성함수,generating_function
확률생성함수,probability_generating_function,PGF
11.1. random number generator (RNG) ¶
random number generation
random number generator (RNG)
=,RNG .
random number generator (RNG)
=,RNG .
REL random_number
https://en.wikipedia.org/wiki/Random_number_generation
https://en.wikipedia.org/wiki/List_of_random_number_generators
random number generator
random number generator
random number generator
https://en.wikipedia.org/wiki/List_of_random_number_generators
random number generator
random number generator
random number generator
rel. randomness_test { randomness test rel. cryptography https://en.wikipedia.org/wiki/Randomness_test randomness test 테스트,test는 검정,test? 판정법,test? }
12. sort / sorting / 정렬 #sort ¶
(대충 생각나는대로,chk) { 키,key를 기준으로(primary_key 말고 secondary_key ...도 있는 경우가 있는데 tbw) , 비교,comparison하여, (근데 비교정렬 이 아닌 경우도 있는데 tbw) 순서,order에 따라, 위치를 바꾸어서(교환, swap, exchange) }
정렬,jeongryeol =정렬,sorting =,sorting =,sort .
sort sort#Noun
sorting sorting#Noun
소팅
정렬,jeongryeol =정렬,sorting =,sorting =,sort .
sort sort#Noun
sorting sorting#Noun
소팅
정렬알고리즘을 분류하는 방법은 매우 다양한데
quick
quicksort quick_sort =,quicksort =,quick_sort ... quicksort
quick sort
REL
pivot - 피벗,pivot
불안정정렬
시간복잡도,time_complexity \Theta(n\log n) O(n^2)
quicksort quick_sort =,quicksort =,quick_sort ... quicksort
quick sort
REL
pivot - 피벗,pivot
불안정정렬
시간복잡도,time_complexity \Theta(n\log n) O(n^2)
13.1. fork (system call) ¶
system_call로서의 fork:
Fork_(system_call)
= https://en.wikipedia.org/wiki/Fork_(system_call)
= https://en.wikipedia.org/wiki/Fork_(system_call)
= https://en.wikipedia.org/wiki/Fork_(system_call)
= https://en.wikipedia.org/wiki/Fork_(system_call)
이것의 응용: fork_bomb
fork_bomb =,fork_bomb =,fork_bomb . fork_bomb
fork_bomb =,fork_bomb =,fork_bomb . fork_bomb
{
fork_bomb
https://ko.wikipedia.org/wiki/포크_폭탄
https://simple.wikipedia.org/wiki/Fork_bomb
https://en.wikipedia.org/wiki/Fork_bomb
fork bomb
"fork bomb"
"fork bomb"
}//fork bomb
fork_bomb
https://ko.wikipedia.org/wiki/포크_폭탄
https://simple.wikipedia.org/wiki/Fork_bomb
https://en.wikipedia.org/wiki/Fork_bomb
DoS (denial_of_service) 공격,attack =,dos =,attack =,dos_attack . {
https://ko.wikipedia.org/wiki/서비스_거부_공격
https://simple.wikipedia.org/wiki/Denial-of-Service_attack
https://en.wikipedia.org/wiki/Denial-of-service_attack
},
resource_starvation =,resource_starvation =,resource_starvation . resource_starvation
{
fork bombhttps://ko.wikipedia.org/wiki/서비스_거부_공격
https://simple.wikipedia.org/wiki/Denial-of-Service_attack
https://en.wikipedia.org/wiki/Denial-of-service_attack
},
resource_starvation =,resource_starvation =,resource_starvation . resource_starvation
{
resource starvation
resource_starvation x 2023-08-25
Resource_starvation redir to Starvation_(computer_science)
resource starvation
resource starvation
"resource starvation"
}resource_starvation x 2023-08-25
Resource_starvation redir to Starvation_(computer_science)
resource starvation
resource starvation
"resource starvation"
fork bomb
"fork bomb"
"fork bomb"
}//fork bomb
15. (tmp, 위 두 sections.) fork vs branch ¶
공통된 뜻은 분기 분리 갈라짐 ... split
반대는 합쳐짐
두 단어 모두 computing에서 많이 쓰이는데 usage 차이가 있는데 확실히 tbw incl. reliable src.
둘다 VCS에서 쓰이는데 vcs에 따라 word usage가 차이가 있을수 있지만 대체로: fork는 한 project 전체가 대상이고 branch는 개발 과정의 한 시점인 특정 작업상태에 대한..? fork를 한다고 하면 대체로 어떤 특정 시점에서 전체 data의 dump를 얻는 것 같던데.
fork는 POSIX system_call 의 하나(for 프로세스,process관리, process_management) / branch는 아님
branch는 CPU(프로세서,process)의 conditional_jump 와 동의어? chk
반대는 합쳐짐
두 단어 모두 computing에서 많이 쓰이는데 usage 차이가 있는데 확실히 tbw incl. reliable src.
둘다 VCS에서 쓰이는데 vcs에 따라 word usage가 차이가 있을수 있지만 대체로: fork는 한 project 전체가 대상이고 branch는 개발 과정의 한 시점인 특정 작업상태에 대한..? fork를 한다고 하면 대체로 어떤 특정 시점에서 전체 data의 dump를 얻는 것 같던데.
fork는 POSIX system_call 의 하나(for 프로세스,process관리, process_management) / branch는 아님
branch는 CPU(프로세서,process)의 conditional_jump 와 동의어? chk
fork가 대체로 더 큰 범위에서 쓰이는 듯? (dump처럼)
fork branch 차이
fork branch 차이
fork branch 차이
software project 전체를 복제해서 다른 길로 가겠다 / wiki에도 쓰임(데이터 전체를 복사해 새 위키를) / cryptocurrency 에도 쓰임.
...fork branch 차이
fork branch 차이
fork branch 차이
18. ambiguity ¶
=,ambiguity .
ambiguity
애매성
애매모호함
모호성
중의성 애매성 (wk)
...
ambiguity
애매성
애매모호함
모호성
중의성 애매성 (wk)
...
chk 나만의생각:
ambiguous_grammar - 문법,grammar
이것은 해석,interpretation의 가능성,possibility의 수(해석하는 경우,case의 수)(해석 가능한 경우의_수,number_of_cases)가 하나냐 둘 이상이냐에(ie 단수냐 복수냐에)관한 것??
Sub:ambiguous_grammar - 문법,grammar
22.1. nodal decomposition ¶
nodal_decomposition =,nodal_decomposition . nodal_decomposition
{
nodal decomposition
https://en.wikipedia.org/wiki/Nodal_decomposition
nodal decomposition
범주론,category_theory
}
{
nodal decomposition
https://en.wikipedia.org/wiki/Nodal_decomposition
nodal decomposition
범주론,category_theory
}
23.1. 확률론 ¶
=확률론,probability_theory =,probability_theory . 확률론 probability_theory
확률론
확률론
확률론 = https://www.kms.or.kr/mathdict/list.html?key=kname&keyword=확률론
{ 2023-11-18 현재 3개
combinatorial probability 조합적 확률론
probability theory 확률론
stochastics 확률론 // stochastics .... stochastics stochastics stochastics stochastics
}
{ 2023-11-18 현재 3개
combinatorial probability 조합적 확률론
probability theory 확률론
stochastics 확률론 // stochastics .... stochastics stochastics stochastics stochastics
}
probability_theory = https://en.wiktionary.org/wiki/probability_theory
Probability_theory
Probability_theory
Probability_theory
Probability_theory
24. prediction / forecasting ¶
=,prediction =,forecasting =,forecast .
예상
예측
예보
....
예상
예측
예보
....
비슷,cmp,mklink: estimation =,estimation .
estimation
tenataive pagename 추정,estimation
(we) "Estimation (or estimating) is the 과정,process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable."
https://en.wikipedia.org/wiki/Estimation
Cmp: 추론,inferencetenataive pagename 추정,estimation
MKL 추정량,estimator ..
이것은 (대개) 완벽할 수 없으므로 approximation 의 일종인가? (we) "Estimation (or estimating) is the 과정,process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable."
https://en.wikipedia.org/wiki/Estimation
https://simple.wikipedia.org/wiki/Prediction
https://simple.wikipedia.org/wiki/Forecasting
https://simple.wikipedia.org/wiki/Forecasting
Forecasting n.
forecast v.
forecast v.
26. closure #closure ¶
관련표현:
closed (특히 prefix. closed_set etc. opp. open_ ... curr at 형용사,adjective?action=highlight&value=closed)
closing
closed (특히 prefix. closed_set etc. opp. open_ ... curr at 형용사,adjective?action=highlight&value=closed)
closing
Sub:
(나중에 logic과 topology의 closure를 나누어야? 아님 필요 없나?)
https://en.wikipedia.org/wiki/Transitive_closure
closure_relation - curr 관계,relation?action=highlight&value=closure_relation
(나중에 logic과 topology의 closure를 나누어야? 아님 필요 없나?)
https://en.wikipedia.org/wiki/Transitive_closure
rel. transitivity / transitive_relation
https://en.wikipedia.org/wiki/Deductive_closurerel deduction ( 연역,deduction ... )
https://en.wikipedia.org/wiki/Symmetric_closurerel. 대칭성,symmetry / smallest symmetric_relation
https://en.wikipedia.org/wiki/Reflexive_closuresmallest reflexive_relation
https://en.wikipedia.org/wiki/Closure_operatorclosure_relation - curr 관계,relation?action=highlight&value=closure_relation
27. 동기화,synchronization ¶
QQQ 동기화,synchronization 성질을 가졌다는 명사형은? 동기성 synchrony synchronism ?
Sub:
=,wait-free_synchronization =,wait-free_synchronization . wait-free_synchronization
=,wait-free_synchronization =,wait-free_synchronization . wait-free_synchronization
wait-free synchronization
http://wiki.c2.com/?WaitFreeSynchronization
wait-free synchronization
"wait-free synchronization"
=,lock-free_synchronization =,lock-free_synchronization . lock-free_synchronizationhttp://wiki.c2.com/?WaitFreeSynchronization
wait-free synchronization
"wait-free synchronization"
lock-free synchronization
http://wiki.c2.com/?LockFreeSynchronization
lock-free synchronization
"lock-free synchronization"
=,lock-based_synchronization =,lock-based_synchronization . lock-based_synchronizationhttp://wiki.c2.com/?LockFreeSynchronization
lock-free synchronization
"lock-free synchronization"
lock-based synchronization
http://wiki.c2.com/?LockBasedSynchronization
"lock-based synchronization"
=,sychronization_strategy =,sychronization_strategy . sychronization_strategyhttp://wiki.c2.com/?LockBasedSynchronization
- aka pessimistic_locking
lock-based synchronization"lock-based synchronization"
sychronization strategy
http://wiki.c2.com/?SynchronizationStrategies
전략,strategy
sychronization strategy
"sychronization strategy"
http://wiki.c2.com/?SynchronizationStrategies
전략,strategy
sychronization strategy
"sychronization strategy"
28. denotation and connotation ¶
denotation
connotation
denotation
connotation
(영어사전)
denotation n.(단어를 통한) 지시, 명시적 의미
connotation n. 함축(된 의미)
connotation
denotation
connotation
(영어사전)
denotation n.(단어를 통한) 지시, 명시적 의미
connotation n. 함축(된 의미)
28.1.1. denotational semantics ¶
denotational_semantics =,denotational_semantics .
https://en.wikipedia.org/wiki/Denotational_semantics
https://en.wikipedia.org/wiki/Denotational_semantics
denotational_semantics_of_the_Actor_model
https://en.wikipedia.org/wiki/Denotational_semantics_of_the_Actor_model
https://en.wikipedia.org/wiki/Denotational_semantics_of_the_Actor_model
actor_model =,actor_model . actor_model {
https://en.wikipedia.org/wiki/Actor_model
actor_model
model
}
https://en.wikipedia.org/wiki/Actor_model
actor_model
model
}
29. natural language ¶
Sub:
자연 언어 이해 natural language understanding
자연 언어 처리 NLP //바로아래
자연 언어 질의 natural language query // via https://terms.naver.com/entry.naver?docId=830352&cid=50376&categoryId=50376
자연 언어 생성 natural language generation //via https://terms.naver.com/entry.naver?docId=830348&cid=50376&categoryId=50376
Opp:
인공어
artificial language
constructued language
conlang
자연 언어 이해 natural language understanding
자연 언어 처리 NLP //바로아래
자연 언어 질의 natural language query // via https://terms.naver.com/entry.naver?docId=830352&cid=50376&categoryId=50376
자연 언어 생성 natural language generation //via https://terms.naver.com/entry.naver?docId=830348&cid=50376&categoryId=50376
Opp:
인공어
artificial language
constructued language
conlang
Up: 언어,language
30. 처리 processing ¶
Sub:
처리장치,processing_unit
처리장치,processing_unit
이때의 unit은 한국어로 단위(단위,unit)보단 장치로 번역한다. (장치,device)
줄여서 처리기,processor와 동의어?
중앙처리장치,central_processing_unit,CPU
텐서처리장치,tensor_processing_unit,TPU
물리처리장치
graphics_processing_unit
자연어처리,natural_language_processing,NLP줄여서 처리기,processor와 동의어?
중앙처리장치,central_processing_unit,CPU
텐서처리장치,tensor_processing_unit,TPU
물리처리장치
graphics_processing_unit
32. hidden Markov model HMM ¶
=,hidden_Markov_model =,HMM .
hidden_Markov_model
HMM
hidden Markov model
hidden_Markov_model
HMM
hidden Markov model
은닉 마르코프 모델|모형
은닉_마르코프_모형 = https://ko.wikipedia.org/wiki/은닉_마르코프_모형
https://en.wikipedia.org/wiki/Hidden_Markov_model
https://en.wikipedia.org/wiki/Hidden_Markov_model
Up: Markov_model
34. Intel_x86 ¶
=,x86 . x86 x86_architecture ?
GDT,global_descriptor_table
LDT,local_descriptor_table
TSS,task_state_segment 태스크,task
call_gate 호출 게이트 / 콜 게이트 호출,call ? 콜,call ? 게이트,gate
task_gate 태스크 게이트 태스크,task
paging - curr at 메모리,memory?action=highlight&value=paging
LDT,local_descriptor_table
TSS,task_state_segment 태스크,task
call_gate 호출 게이트 / 콜 게이트 호출,call ? 콜,call ? 게이트,gate
task_gate 태스크 게이트 태스크,task
paging - curr at 메모리,memory?action=highlight&value=paging
descriptor
하지만 LDT 0번 디스크립터는 valid entry.
서술자 기술자 or 디스크립터 ...?
null_descriptor =,null_descriptor . null_descriptor null_descriptor
null descriptor
descriptor_table =,descriptor_table . descriptor_table
descriptor table
GDT의 0번 디스크립터는 unusable.null_descriptor =,null_descriptor . null_descriptor null_descriptor
null descriptor
descriptor_table =,descriptor_table . descriptor_table
descriptor table
하지만 LDT 0번 디스크립터는 valid entry.
rel. description
34.1.1. real mode ¶
35.1. disk geometry/addressing ¶
CHS cylinder_head_sector
LBA logical_block_addressing
LBA logical_block_addressing
partition
{
디스크 사이즈 제한
MBR partition table은 섹터가 512바이트일 때 블럭 주소 한계가 232라서 2 TiB 제한.
GPT는 섹터가 512바이트일 때 264라서 8 ZiB 제한.
(table)
type
GPT = GUID_partition_tabletype
{
디스크 사이즈 제한
MBR partition table은 섹터가 512바이트일 때 블럭 주소 한계가 232라서 2 TiB 제한.
GPT는 섹터가 512바이트일 때 264라서 8 ZiB 제한.
LBA 0 : protective MBR. (무엇?)
LBA 1 : GPT header
LBA 2 :
}
LBA 1 : GPT header
LBA 2 :
}
35.2. boot booting ¶
=,boot =,booting .
boot_manager
MBR master_boot_record
MBR master_boot_record
boot_image
rel. disk_image
boot_recordboot_sector
VBR volume_boot_record
{
AKA volume boot sector, partition boot record, partition boot sector
}
{
AKA volume boot sector, partition boot record, partition boot sector
}
EBR extended_boot_record
{
AKA EPBR(extended partition boot record)
}
{
AKA EPBR(extended partition boot record)
}
BPB BIOS_parameter_block
EBPB extended_BIOS_parameter_block
EBPB extended_BIOS_parameter_block
36.2. light cone ¶
light cone
null cone
light_cone =,light_cone . null_cone =,null_cone .
null cone
light_cone =,light_cone . null_cone =,null_cone .
"light cone (or "null cone")" ... 널,null
상대론 relativity
사건,event
시공간,spacetime =,spacetime . spacetime { spacetime 시공간 시공 (시간,time + 공간,space ?)... spacetime Up: physics { RR 물리physics 있음. VG 물리학,physics 있음. 물리,physics는 어떨지? }//physics }//spacetime
causality
빛,light
... btw, Null_cone redir to Null_vector
relnull_cone = isotropic_cone - rel. null_vector isotropic_vector [1]
pagename은 널벡터,null_vector ... 벡터공간,vector_space의 zero_element =,zero_element . zero_element { zero element : 영원 영원소 중에? zero element says: "영원(소)" .... zero_element zero_element .... 영,zero 원소,element }인 영벡터,zero_vector와 다른 것.
상대론 relativity
사건,event
시공간,spacetime =,spacetime . spacetime { spacetime 시공간 시공 (시간,time + 공간,space ?)... spacetime Up: physics { RR 물리physics 있음. VG 물리학,physics 있음. 물리,physics는 어떨지? }//physics }//spacetime
causality
빛,light
(중요하지 않은건 ADDHERE ... 그렇지 않은건 위쪽에.)
40. etc ¶
discharging:
$\displaystyle q=q_0e^{-\frac{t}{RC}}$
$\displaystyle V=V_0e^{-\frac{t}{RC}}$
$\displaystyle q=q_0e^{-\frac{t}{RC}}$
$\displaystyle V=V_0e^{-\frac{t}{RC}}$
limits vs nolimits
$\displaystyle \limits\int_a^bf(x)dx$
$\displaystyle \nolimits\int_a^bf(x)dx$
$\displaystyle \limits\int_a^bf(x)dx$
$\displaystyle \nolimits\int_a^bf(x)dx$
$\displaystyle |\limits_a^b$
$\displaystyle |\nolimits_a^b$
$\displaystyle |\nolimits_a^b$
영인자만들기:
$\displaystyle \begin{pmatrix}a&a\\b&b\end{pmatrix}\begin{pmatrix}x&-y\\-x&y\end{pmatrix},\; \begin{pmatrix}1&1\\-1&-1\end{pmatrix}\begin{pmatrix}1&1\\-1&-1\end{pmatrix}$
영인자
$\displaystyle \begin{pmatrix}a&a\\b&b\end{pmatrix}\begin{pmatrix}x&-y\\-x&y\end{pmatrix},\; \begin{pmatrix}1&1\\-1&-1\end{pmatrix}\begin{pmatrix}1&1\\-1&-1\end{pmatrix}$
영인자
41. TeX의 그리스 문자 ¶
대문자 명칭 나열:
$\displaystyle \Alpha \Beta \Gamma \Delta \Epsilon \Zeta \Eta \Theta \Iota \Kappa \Lambda \Mu \Nu \Xi \Omicron \Pi \Rho \Sigma \Tau \Upsilon \Phi \Chi \Psi \Omega$
소문자 명칭 나열:
$\displaystyle \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi \omicron \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega$
$\displaystyle \Alpha \Beta \Gamma \Delta \Epsilon \Zeta \Eta \Theta \Iota \Kappa \Lambda \Mu \Nu \Xi \Omicron \Pi \Rho \Sigma \Tau \Upsilon \Phi \Chi \Psi \Omega$
소문자 명칭 나열:
$\displaystyle \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi \omicron \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega$
TeX는 그리스 문자를 표현할 때 로마자와 모양이 같은 것을 재활용한다. 따라서 그리스 대문자 목록을 표현하려면
$\displaystyle A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega$
소문자 목록은
$\displaystyle \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega$
var- 소문자 목록은
$\displaystyle \epsilon-\varepsilon/\theta-\vartheta/\pi-\varpi/\rho-\varrho/\sigma-\varsigma/\phi-\varphi$
$\displaystyle A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega$
소문자 목록은
$\displaystyle \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega$
var- 소문자 목록은
$\displaystyle \epsilon-\varepsilon/\theta-\vartheta/\pi-\varpi/\rho-\varrho/\sigma-\varsigma/\phi-\varphi$
표준 (italic)
$\displaystyle ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789$
$\displaystyle A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi$
을 다음과 같이 다양하게 표현을 시도, 아래 렌더링에서 어떤 꼴이 표현 지원되거나 지원되지 않는 지 확인 가능
$\displaystyle ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789$
$\displaystyle A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi$
을 다음과 같이 다양하게 표현을 시도, 아래 렌더링에서 어떤 꼴이 표현 지원되거나 지원되지 않는 지 확인 가능
mathcal:
$\displaystyle \mathcal{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathcal{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
$\displaystyle \mathcal{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathcal{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
mathrm:
$\displaystyle \mathrm{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathrm{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
$\displaystyle \mathrm{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathrm{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
mathbb:
$\displaystyle \mathbb{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathbb{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
$\displaystyle \mathbb{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathbb{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
mathbf:
$\displaystyle \mathbf{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathbf{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
$\displaystyle \mathbf{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathbf{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
mathscr:
$\displaystyle \mathscr{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathscr{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
$\displaystyle \mathscr{ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz 0123456789}$
$\displaystyle \mathscr{A B \Gamma \Delta E Z H \Theta I K \Lambda M N \Xi O \Pi P \Sigma T \Upsilon \Phi X \Psi \Omega \alpha \beta \gamma \delta \epsilon \zeta \eta \theta \iota \kappa \lambda \mu \nu \xi o \pi \rho \sigma \tau \upsilon \phi \chi \psi \omega \varepsilon\vartheta\varpi\varrho\varsigma\varphi}$
mathsf, mathtt는 전혀 지원 안하는 듯
43. 이상익 ¶
VG: 정수론,number_theory
$\displaystyle A=B \cdot Q+R, \quad\quad 0 \le R < B$
에서$\displaystyle R=A-B\left\lfloor \frac{A}{B} \right\rfloor$
// rel : 모듈로,modulo > modulo_operation https://proofwiki.org/wiki/Definition:Modulo_Operation44.1. TBD 1 ¶
맨 뒤에 ,ABBR postfix suffix 관습은 유지할 것인가 말것인가
abbr만으로 충분하다면 그것만 쓸것인가 아님 말것인가
...TBD
abbr만으로 충분하다면 그것만 쓸것인가 아님 말것인가
...TBD
일단 입출력은 입출력,IO로 했는데 편의상
45. tmp 1 ¶
tmp/ written by dr j. lee, https://cafe.naver.com/kpope/931
라그랑지안,Lagrangian은 먼저 $\displaystyle F=ma$ 에서 바로 나옵니다.
$\displaystyle F=-\nabla U$ 이고 $\displaystyle ma=m\ddot{x}=\frac{d}{dt} [m\dot{x}]$ 입니다.
그런데 $\displaystyle m\dot{x}=\frac{\partial}{\partial \dot{x}} \frac{1}{2}m\dot{x}^2$
이므로 $\displaystyle m\dot{x}=\frac{\partial}{\partial \dot{x}} T$ 입니다.
Cartesian coordinate에서는 kinetic energy T가 오직 $\displaystyle \dot{x}$ dependent
potential energy $\displaystyle V$ 가 오직 $\displaystyle x$ dependent (물론 velocity independent potential 에서)(
그러니
$\displaystyle F=ma$ 는 Euler-Lagrange equation과 equivalent합니다.
$\displaystyle \left[ \frac{\partial}{\partial x}-\frac{d}{dt}\frac{\partial}{\partial\dot{x}}\right](T-V)$
문제는 이것이 least-action principle로부터 유도되는 이유가 key입니다.
당시 Euler는 brachistochrone 문제들을 통해 이미 최소값과 관련한 calculus of variation 을 개발해 놓았고
이것이 이렇게 응용되어 결국 Hamilton's least-action principle로 완성되게 됩니다.
$\displaystyle F=-\nabla U$ 이고 $\displaystyle ma=m\ddot{x}=\frac{d}{dt} [m\dot{x}]$ 입니다.
그런데 $\displaystyle m\dot{x}=\frac{\partial}{\partial \dot{x}} \frac{1}{2}m\dot{x}^2$
이므로 $\displaystyle m\dot{x}=\frac{\partial}{\partial \dot{x}} T$ 입니다.
Cartesian coordinate에서는 kinetic energy T가 오직 $\displaystyle \dot{x}$ dependent
potential energy $\displaystyle V$ 가 오직 $\displaystyle x$ dependent (물론 velocity independent potential 에서)(
그러니
$\displaystyle F=ma$ 는 Euler-Lagrange equation과 equivalent합니다.
당시 Euler는 brachistochrone 문제들을 통해 이미 최소값과 관련한 calculus of variation 을 개발해 놓았고
이것이 이렇게 응용되어 결국 Hamilton's least-action principle로 완성되게 됩니다.
46. tmp2 ¶
2024-06-06
Prof. Michael Bronstein (CS, University of Oxford, DeepMind prof. -> https://www.cs.ox.ac.uk/news/1996-full.html ) delivered a lecture titled
Geometric Deep Learning: From Euclid to Drug Design
as part of the Hot Topics in Computing Series at CSAIL.
Prof. Michael Bronstein (CS, University of Oxford, DeepMind prof. -> https://www.cs.ox.ac.uk/news/1996-full.html ) delivered a lecture titled
Geometric Deep Learning: From Euclid to Drug Design
as part of the Hot Topics in Computing Series at CSAIL.
1:07
He's very well known for dynamic graph CNNs for learning on point clouds. // dynamic_graph_CNN 점구름,point_cloud
He's very well known for dynamic graph CNNs for learning on point clouds. // dynamic_graph_CNN 점구름,point_cloud
3:30
Hermann_Weyl: "Symmetry, as wide or as narrow as you may define its meaning, is one idea by which man through the ages has tried to comprehend and create order, beauty, and perfection" // 대칭성,symmetry
4:00
플라톤,Plato (~370 BC)의 Platonic_solid (플라톤 입체 or 플라톤 다면체 ... 입체,solid) 언급
4:44
에우클레이데스,Euclid (~300 BC)의 5th postulate, and 19세기에 나타난 비유클리드 언급
Hermann_Weyl: "Symmetry, as wide or as narrow as you may define its meaning, is one idea by which man through the ages has tried to comprehend and create order, beauty, and perfection" // 대칭성,symmetry
4:00
플라톤,Plato (~370 BC)의 Platonic_solid (플라톤 입체 or 플라톤 다면체 ... 입체,solid) 언급
4:44
에우클레이데스,Euclid (~300 BC)의 5th postulate, and 19세기에 나타난 비유클리드 언급
entire zoo of different geometries
affine_geometry 아핀기하학,affine_geometry
projective_geometry 사영기하학,projective_geometry
- Euclidean
- affine
- projective
affine_geometry 아핀기하학,affine_geometry
projective_geometry 사영기하학,projective_geometry
이런 상황에서 '기하학을 어떻게 정의할 것인가'의 문제가 제기. (어떤 기하학이 다른 것보다 일반적인가?)
paradigm shift는 젊은 Felix_Klein (1872) { 23세에 독일 Erlangen 대학교 교수. }로부터 왔는데
그는 radically new way of thinking of geometry in terms of invariances 를 제안하였다. // 불변성,invariance
geometric object를 group of transformations // 기하학적 대상,object: 군,group of 변환,transformation
-> Erlangen_program. 에를랑겐_프로그램 Erlangen_program {Topics: 동차공간,homogeneous_space }
그는 radically new way of thinking of geometry in terms of invariances 를 제안하였다. // 불변성,invariance
geometric object를 group of transformations // 기하학적 대상,object: 군,group of 변환,transformation
-> Erlangen_program. 에를랑겐_프로그램 Erlangen_program {Topics: 동차공간,homogeneous_space }
6:00
ex.
Euclidean geometry
E(3)
E(3)
Emmy_Noether: 뇌터_정리,Noether_theorem: principles of symmetry에서 보존법칙,conservation_law을 도출할 수 있음을 보였음.
like: conservation of energy comes from symmetry of time.
(에너지,energy 보존은 시간,time 대칭에서)
이것이 나중에 발전하여 입자물리학,particle_physics의 standard_model.
like: conservation of energy comes from symmetry of time.
(에너지,energy 보존은 시간,time 대칭에서)
이것이 나중에 발전하여 입자물리학,particle_physics의 standard_model.
6:56
물리에선 external vs internal symmetry를 구분
external symmetries of the spacetime - what is called the 푸앵카레_군,Poincare_group, that gives rise to the [[
external symmetry - R1,3 O(1,3) ...
internal symmetry - U(1) SU(2) SU(3) ...
물리에선 external vs internal symmetry를 구분
external symmetries of the spacetime - what is called the 푸앵카레_군,Poincare_group, that gives rise to the [[
external symmetry - R1,3 O(1,3) ...
internal symmetry - U(1) SU(2) SU(3) ...
7:30
"It is only slightly overstating the case to say that Physics is the study of symmetry" - P. Anderson // 대칭성,symmetry
"It is only slightly overstating the case to say that Physics is the study of symmetry" - P. Anderson // 대칭성,symmetry
그럼 이게 ML(기계학습,machine_learning)과 무슨 관련인가?
We have historically different architectures of 신경망,neural_networks such as
다른 context에서 온 다른 architecture이다.
우린 여기서 공통분모,common_denominator를 찾고 싶다. (이미 있던 것들을) 설명하고, 같은 원리에 기반해 새로운 architecture를 설계(design)하는 걸 하고 싶은데, 이게 바로 GNN이다.
We have historically different architectures of 신경망,neural_networks such as
다른 context에서 온 다른 architecture이다.
우린 여기서 공통분모,common_denominator를 찾고 싶다. (이미 있던 것들을) 설명하고, 같은 원리에 기반해 새로운 architecture를 설계(design)하는 걸 하고 싶은데, 이게 바로 GNN이다.
cont 8m
47. allocator #allocator ¶
할당자,allocator ? 할당,allocation하는
=할당자,allocator =,allocator =,allocator . allocator
allocator = https://en.wiktionary.org/wiki/allocator (볼필요x easy)
allocator
allocator
allocator
=할당자,allocator =,allocator =,allocator . allocator
allocator
allocator
allocator
----