2023年2月18日 @ 学習院大学
学習院桜友会寄付講座(生命情報社会学)シンポジウム
X-informatics 〜巡り会うデータサイエンス〜
https://www-cc.gakushuin.ac.jp/~support/symp/2023xinformatics/
⾒
https://itakigawa.github.io/
2023.2.18 @
(WPI-ICReDD)
⾒
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(10 )
/ (7 )
(7 )
JST (3.5 )
AIP iPS G (4 )
(4 )
(0.5 )
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( )
(Bioinformatics)
Materials Informatics
( )
稿
3
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(g) (cm)
(g) (cm)
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
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(g) (cm)
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
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(g) (cm)
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
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(g) (cm)
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(cm)
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(g) (cm)
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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90 112.5 135 157.5 180
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(g)
(cm)
む
む
(g) (cm)
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
む
む
(cm)
(g)
む
む
む
む
or
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
む
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or
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
む
む
む
or
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
む
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or
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
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or
5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
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5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
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5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
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む
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5 6.25 7.5 8.75 10
90 112.5 135 157.5 180
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(g)
(cm)
(cm)
(g)
む
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( )
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( )
( )
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x
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y 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
y
AAAB+nicdVDLSsNAFJ34rPVVdelmsAh1E5L06a7oxmUF+4A2lMl00g6dScLMRAixv+BW1+7ErT/j0j9x0lawogcuHM65l3vv8SJGpbKsD2NtfWNzazu3k9/d2z84LBwdd2QYC0zaOGSh6HlIEkYD0lZUMdKLBEHcY6TrTa8zv3tPhKRhcKeSiLgcjQPqU4xUJkWl5GJYKFrmZaPmVB1omZZVd8q1jDj1ilOGtlYyFMESrWHhczAKccxJoDBDUvZtK1JuioSimJFZfhBLEiE8RWPS1zRAnEg3nd86g+daGUE/FLoCBefqz4kUcSkT7ulOjtRE/vYy8S+vHyu/4aY0iGJFArxY5McMqhBmj8MRFQQrlmiCsKD6VognSCCsdDwrWzw+05l8Pw7/Jx3HtGtm9bZSbF4t08mBU3AGSsAGddAEN6AF2gCDCXgET+DZeDBejFfjbdG6ZixnTsAKjPcvl+qUwA==
p(y)
AAAB+XicbVDLSgNBEOz1GeMr6tHLYBDEQ9gVX8egF48RzQOSNcxOZpMhM7PLzKywLPkEr3r2Jl79Go/+iZNkDyaxoKGo6qa7K4g508Z1v52l5ZXVtfXCRnFza3tnt7S339BRogitk4hHqhVgTTmTtG6Y4bQVK4pFwGkzGN6O/eYzVZpF8tGkMfUF7ksWMoKNlR7Sp9NuqexW3AnQIvFyUoYctW7pp9OLSCKoNIRjrdueGxs/w8owwumo2Ek0jTEZ4j5tWyqxoNrPJqeO0LFVeiiMlC1p0ET9O5FhoXUqAtspsBnoeW8s/ue1ExNe+xmTcWKoJNNFYcKRidD4b9RjihLDU0swUczeisgAK0yMTWdmSyBGNhNvPoFF0jireJeVi/vzcvUmT6cAh3AEJ+DBFVThDmpQBwJ9eIFXeHMy5935cD6nrUtOPnMAM3C+fgGxe5Q5
y⇤
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
EI =
Z 1
y⇤
y · p(y)dy
Expected Improvement (EI)
Machine Learning Prediction
Prediction Interval
:
UQ ( )
=
ダ
ダ (data leakage)
=
ダ
ダ (data leakage)
テ Training ( )
=
ダ
ダ (data leakage)
テ Training ( ) デ Validation ( )
=
ダ
ダ (data leakage)
テ Training ( ) デ Validation ( )
=
ダ
ダ (data leakage)
テ Training ( ) デ Validation ( )
=
ダ
ダ (data leakage)
テ Training ( ) デ Validation ( ) ト Test ( )
=
( )
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x1
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x2
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y
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f
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f
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y
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x1 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
x2
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x1 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
x2
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y
( )
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x1
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x2
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y
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y
‣
(= )
(x , x ) y
( )
( )
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x1
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x2
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y
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f
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f
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y
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x2
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x2
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y
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(x , x ) y
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y (x , x )
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x1
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x2
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y
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f
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f
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
y
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x1 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
x2
⾒ ( )
N = = N = = N = =
Fisher
( )
. (Replication)
⾒ ( )
. (Local Control)
. (Randomization) (Fisher )
Data Leakage
:
:
( ) ⾒
༗અ
Herbert Simon
Simon HA, Machine Discovery. ( )
Langley PW, Simon HA, Bradshaw G, Zytkow JM, Scienti c Discovery:
Computational Explorations of the Creative Process ( ).
, . (1996)
, . (2001)
:
( ) ⾒
༗અ
Herbert Simon
Simon HA, Machine Discovery. ( )
Langley PW, Simon HA, Bradshaw G, Zytkow JM, Scienti c Discovery:
Computational Explorations of the Creative Process ( ).
, . (1996)
, . (2001)
3
.
.
( )
.
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
x
AAAB93icbVDLSgNBEOyNrxhfUY9eFoPgKeyKr2PQi8cEzAOSJcxOepMhM7PLzKywhHyBVz17E69+jkf/xEmyBxMtaCiquunuChPOtPG8L6ewtr6xuVXcLu3s7u0flA+PWjpOFcUmjXmsOiHRyJnEpmGGYydRSETIsR2O72d++wmVZrF8NFmCgSBDySJGibFSI+uXK17Vm8P9S/ycVCBHvV/+7g1imgqUhnKiddf3EhNMiDKMcpyWeqnGhNAxGWLXUkkE6mAyP3Tqnlll4EaxsiWNO1d/T0yI0DoToe0UxIz0qjcT//O6qYlugwmTSWpQ0sWiKOWuid3Z1+6AKaSGZ5YQqpi91aUjogg1NpulLaGY2kz81QT+ktZF1b+uXjUuK7W7PJ0inMApnIMPN1CDB6hDEyggPMMLvDqZ8+a8Ox+L1oKTzxzDEpzPH5Ack50=
y
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
x
AAAB93icbVDLSgNBEOyNrxhfUY9eFoPgKeyKr2PQi8cEzAOSJcxOepMhM7PLzKywhHyBVz17E69+jkf/xEmyBxMtaCiquunuChPOtPG8L6ewtr6xuVXcLu3s7u0flA+PWjpOFcUmjXmsOiHRyJnEpmGGYydRSETIsR2O72d++wmVZrF8NFmCgSBDySJGibFSI+uXK17Vm8P9S/ycVCBHvV/+7g1imgqUhnKiddf3EhNMiDKMcpyWeqnGhNAxGWLXUkkE6mAyP3Tqnlll4EaxsiWNO1d/T0yI0DoToe0UxIz0qjcT//O6qYlugwmTSWpQ0sWiKOWuid3Z1+6AKaSGZ5YQqpi91aUjogg1NpulLaGY2kz81QT+ktZF1b+uXjUuK7W7PJ0inMApnIMPN1CDB6hDEyggPMMLvDqZ8+a8Ox+L1oKTzxzDEpzPH5Ack50=
y
A.
Two Cultures:
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Data Modeling Algorithmic Modeling 2
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Data Modeling Algorithmic Modeling 2
( )
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Data Modeling Algorithmic Modeling 2
( )
CP
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Data Modeling Algorithmic Modeling 2
( )
CP
2001 20
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Data Modeling Algorithmic Modeling 2
( )
CP
2001 20
Cox Efron ( )
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Data Modeling Algorithmic Modeling 2
( )
CP
2001 20
Cox Efron ( )
20話 2021 Observational Studies
Leo Breiman, Statistical Modeling: The Two Cultures. (with comments and a rejoinder by
the author), Statistical Science, 16(3): 199-231 (August 2001)
https://doi.org/10.1214/ss/1009213726
Two Cultures:
Breiman's main point is: If you want prediction, do prediction for its own sake
and forget about the illusion of representing nature. (Judea Pearl)
https://doi.org/10.1353/obs.2021.0008
Two Cultures:
Breiman's main point is: If you want prediction, do prediction for its own sake
and forget about the illusion of representing nature. (Judea Pearl)
https://doi.org/10.1353/obs.2021.0008
Three Lessons
There have been particularly exciting developments in the last ﬁve years.
What has been learned? The three lessons that seem most important to one:
Rashomon: the multiplicity of good models;
Occam: the conﬂict between simplicity and accuracy;
Bellman: dimensionality—curse or blessing.
Rashomon: the multiplicity of good models
Ϳʲᤵʳͷதʢͳ͔ʣ
ᶄ (ևཾ೭հͷ࡞ʮᤵͷதʯ͔Β) ؔऀͷ͍͏͜ͱ͕৯͍ҧͬͯɺਅ૬͕Θ͔Βͳ͍
͜ͱΛ͍͏ɻʮਅ૬ᤵͷதͩʯ(ਫ਼બ൛ ຊࠃޠେࣙయΑΓ)ʢ
Rashomon 1950
Rashomon: the multiplicity of good models
Ϳʲᤵʳͷதʢͳ͔ʣ
ᶄ (ևཾ೭հͷ࡞ʮᤵͷதʯ͔Β) ؔऀͷ͍͏͜ͱ͕৯͍ҧͬͯɺਅ૬͕Θ͔Βͳ͍
͜ͱΛ͍͏ɻʮਅ૬ᤵͷதͩʯ(ਫ਼બ൛ ຊࠃޠେࣙయΑΓ)ʢ
Rashomon 1950
Rashomon E ect ( ):
Rashomon: the multiplicity of good models
Ϳʲᤵʳͷதʢͳ͔ʣ
ᶄ (ևཾ೭հͷ࡞ʮᤵͷதʯ͔Β) ؔऀͷ͍͏͜ͱ͕৯͍ҧͬͯɺਅ૬͕Θ͔Βͳ͍
͜ͱΛ͍͏ɻʮਅ૬ᤵͷதͩʯ(ਫ਼બ൛ ຊࠃޠେࣙయΑΓ)ʢ
Rashomon 1950
Rashomon E ect ( ):
⾒ ( )
Rashomon: the multiplicity of good models
Ϳʲᤵʳͷதʢͳ͔ʣ
ᶄ (ևཾ೭հͷ࡞ʮᤵͷதʯ͔Β) ؔऀͷ͍͏͜ͱ͕৯͍ҧͬͯɺਅ૬͕Θ͔Βͳ͍
͜ͱΛ͍͏ɻʮਅ૬ᤵͷதͩʯ(ਫ਼બ൛ ຊࠃޠେࣙయΑΓ)ʢ
Rashomon 1950
Rashomon E ect ( ):
⾒ ( )
( )
Rashomon: the multiplicity of good models
Underspeci cation
(specify )
( )
Rashomon: the multiplicity of good models
Underspeci cation
(specify )
( )
Underspeci cation
Google
Occam: the conflict between simplicity and accuracy
ResNet : 2600
ResNet : 4500
E cientNet-B : 6600
VGG : 1 4400
⾒
20×20 1200
1000×1000 300
-layer, -heads BERT: 1 1000
-layer, -heads BERT: 3 3600
GPT- XL: 15 5800
GPT- : 1750
ダ
( )
ダ
Occam: the conflict between simplicity and accuracy
ResNet : 2600
ResNet : 4500
E cientNet-B : 6600
VGG : 1 4400
⾒
20×20 1200
1000×1000 300
-layer, -heads BERT: 1 1000
-layer, -heads BERT: 3 3600
GPT- XL: 15 5800
GPT- : 1750
ダ
( )
ダ
( )
Bellman: dimensionality curse or blessing
( ⾒ )
Bellman: dimensionality curse or blessing
( ⾒ )
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1
AAAChHichVHLSsNAFD2Nr/ps1Y3gRiwVF1JutD5wIUU3LltrVdAiSZzW0DQJSVqoxR/QreLClYIL8QP8ADf+gAs/QVxWcOPC2zQgWtQbJnPmzD13zsxVbUN3PaLnkNTR2dXdE+7t6x8YHIpEh0e2XKviaCKnWYbl7KiKKwzdFDlP9wyxYztCKauG2FZLa8397apwXN0yN72aLfJlpWjqBV1TPKYy8n40RgnyY6IdyAGIIYi0Fb3HHg5gQUMFZQiY8BgbUODytwsZBJu5POrMOYx0f1/gGH2srXCW4AyF2RL/i7zaDViT182arq/W+BSDh8PKCcTpiW6pQY90Ry/08Wutul+j6aXGs9rSCns/cjKWff9XVebZw+GX6k/PHgpY8r3q7N32meYttJa+enTRyC5vxOtTdE2v7P+KnumBb2BW37SbjNi4/MOPyl74xbhB8s92tIOt2YS8kEhmkrHUatCqMMYxiWnuxyJSWEcaOa4vcIoznEvd0ow0J823UqVQoBnFt5BWPgE/Y4+x
1
) 1 1 ( d )
Bellman: dimensionality curse or blessing
( ⾒ )
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0.5
p
d
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
1
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
1
) 1 1 ( d )
Bellman: dimensionality curse or blessing
( ⾒ )
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
0.5
p
d
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
1
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
1
) 1 1 ( d )
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
d = 2
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
0.5
p
2
Bellman: dimensionality curse or blessing
( ⾒ )
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
0.5
p
d
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
1
AAAChHichVHLSsNAFD2Nr/ps1Y3gRiwVF1JutD5wIUU3LltrVdAiSZzW0DQJSVqoxR/QreLClYIL8QP8ADf+gAs/QVxWcOPC2zQgWtQbJnPmzD13zsxVbUN3PaLnkNTR2dXdE+7t6x8YHIpEh0e2XKviaCKnWYbl7KiKKwzdFDlP9wyxYztCKauG2FZLa8397apwXN0yN72aLfJlpWjqBV1TPKYy8n40RgnyY6IdyAGIIYi0Fb3HHg5gQUMFZQiY8BgbUODytwsZBJu5POrMOYx0f1/gGH2srXCW4AyF2RL/i7zaDViT182arq/W+BSDh8PKCcTpiW6pQY90Ry/08Wutul+j6aXGs9rSCns/cjKWff9XVebZw+GX6k/PHgpY8r3q7N32meYttJa+enTRyC5vxOtTdE2v7P+KnumBb2BW37SbjNi4/MOPyl74xbhB8s92tIOt2YS8kEhmkrHUatCqMMYxiWnuxyJSWEcaOa4vcIoznEvd0ow0J823UqVQoBnFt5BWPgE/Y4+x
1
) 1 1 ( d )
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
d = 2
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
0.5
p
2
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
d = 4
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
1
Bellman: dimensionality curse or blessing
( ⾒ )
AAACjnichVHNSgJRFD5Of2Y/Wm2CNpIYreQYZhFEUhuX/uQPqMjMeLPBcWaauQomvkD7aBEUBS2iB+gB2vQCLXyEaGnQpkXHcSBKsjPcud/97vnO/e49kqEqFkfsuoSx8YnJKfe0Z2Z2bt7rW1jMWnrDlFlG1lXdzEuixVRFYxmucJXlDZOJdUllOal20N/PNZlpKbp2yFsGK9XFqqYcKbLIiSpgaLNonZi8XemUfQEMoR3+YRB2QACcSOi+RyhCBXSQoQF1YKABJ6yCCBZ9BQgDgkFcCdrEmYQUe59BBzykbVAWowyR2Br9q7QqOKxG635Ny1bLdIpKwySlH4L4gvfYw2d8wFf8/LNW267R99KiWRpomVH2ni2nP/5V1WnmcPytGumZwxFs214V8m7YTP8W8kDfPL3opXdSwfYa3uIb+b/BLj7RDbTmu3yXZKnLEX4k8kIvRg0K/27HMMhuhMLRUCQZCcT2nVa5YQVWYZ36sQUxiEMCMvaLnsMVXAs+ISrsCnuDVMHlaJbgRwjxLwzik/k=
0.5
p
d
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
1
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
1
) 1 1 ( d )
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
d = 2
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
0.5
p
2
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
d = 4
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
1
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
d > 4
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
0.5
p
d
Bellman: dimensionality curse or blessing
( ⾒ )
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
0.5
p
d
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
1
AAAChHichVHLSsNAFD2Nr/ps1Y3gRiwVF1JutD5wIUU3LltrVdAiSZzW0DQJSVqoxR/QreLClYIL8QP8ADf+gAs/QVxWcOPC2zQgWtQbJnPmzD13zsxVbUN3PaLnkNTR2dXdE+7t6x8YHIpEh0e2XKviaCKnWYbl7KiKKwzdFDlP9wyxYztCKauG2FZLa8397apwXN0yN72aLfJlpWjqBV1TPKYy8n40RgnyY6IdyAGIIYi0Fb3HHg5gQUMFZQiY8BgbUODytwsZBJu5POrMOYx0f1/gGH2srXCW4AyF2RL/i7zaDViT182arq/W+BSDh8PKCcTpiW6pQY90Ry/08Wutul+j6aXGs9rSCns/cjKWff9XVebZw+GX6k/PHgpY8r3q7N32meYttJa+enTRyC5vxOtTdE2v7P+KnumBb2BW37SbjNi4/MOPyl74xbhB8s92tIOt2YS8kEhmkrHUatCqMMYxiWnuxyJSWEcaOa4vcIoznEvd0ow0J823UqVQoBnFt5BWPgE/Y4+x
1
) 1 1 ( d )
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
d = 2
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
0.5
p
2
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
d = 4
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
1
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
d > 4
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
0.5
p
d
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
> 1
!?
Bellman: dimensionality curse or blessing
( ⾒ )
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
0.5
p
d
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
1
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
1
) 1 1 ( d )
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
d = 2
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
0.5
p
2
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
d = 4
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
1
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
d > 4
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
0.5
p
d
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
> 1
!?
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
V (d) =
⇡ d
2
d
2
· d
2
! 0 (d ! 1)
=
=
d
AAAB/XicbVDLSgNBEOz1GeMr6tHLYBA8hV3xdRGCXjxGMA9I1jA7O5sMmZldZmaFsAS/wauevYlXv8Wjf+Ik2YNJLGgoqrrp7goSzrRx3W9naXlldW29sFHc3Nre2S3t7Td0nCpC6yTmsWoFWFPOJK0bZjhtJYpiEXDaDAa3Y7/5RJVmsXwww4T6AvckixjBxkpN7zFE18jrlspuxZ0ALRIvJ2XIUeuWfjphTFJBpSEca9323MT4GVaGEU5HxU6qaYLJAPdo21KJBdV+Njl3hI6tEqIoVrakQRP170SGhdZDEdhOgU1fz3tj8T+vnZroys+YTFJDJZkuilKOTIzGv6OQKUoMH1qCiWL2VkT6WGFibEIzWwIxspl48wksksZpxbuonN+flas3eToFOIQjOAEPLqEKd1CDOhAYwAu8wpvz7Lw7H87ntHXJyWcOYAbO1y9Fl5UB
1d = 1
Bellman: dimensionality curse or blessing
⾒ ( )
Bellman: dimensionality curse or blessing
⾒ ( )
. (Lipschitz )
⾒ ( ) d
d= 100 (10 )
d= 10 =100
Bellman: dimensionality curse or blessing
⾒ ( )
. (Lipschitz )
⾒ ( ) d
d= 100 (10 )
d= 10 =100
( )
. (d> )
3
.
.
( )
.
Informatics
( )
⾒
Informatics
( )
⾒
⾒ (Herbert Simon!)
⾒ ( )
Informatics
( )
⾒
⾒ (Herbert Simon!)
⾒ ( )
⾒
( )
( )
X Y
Y
( )
X Y
Y
( )
X Y
Y
vs
vs
(= )
vs
(= )
• “Theory-driven models can be wrong. But data-driven models cannot be wrong or
right. Data-driven are not trying to describe an underlying reality.”
David Hand, KDD2018 (Keynote Talk)
http://videolectures.net/kdd2018_hand_data_science/
vs
(= )
• “Theory-driven models can be wrong. But data-driven models cannot be wrong or
right. Data-driven are not trying to describe an underlying reality.”
David Hand, KDD2018 (Keynote Talk)
http://videolectures.net/kdd2018_hand_data_science/
⾒
( )
⾒
Universal Approximation Theorem
⾒
( )
Blackbox vs
⾒
⾒
Universal Approximation Theorem
⾒
( )
Blackbox vs
⾒
⾒
Universal Approximation Theorem
⾒
( )
Blackbox vs
Physics-informed ML, Geometric ML, Causal ML
https://doi.org/10.1038/s42254-021-00314-5
×
×
×
⾒ (NP-hard )
Schrittweiser et al. Mastering Atari, Go, chess and shogi by planning with a learned model.
(“MuZero”, Nature, 2020)
Davies et al. Advancing mathematics by guiding human intuition with AI. (Nature, 2021)
Fawzi et al. Discovering faster matrix multiplication algorithms with reinforcement learning.
(“AlphaTensor”, Nature, 2022)
×
closed /
3
⾒
.
.
( )
.
( )