Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
編入試験への準備と編入後の生活 (Ver.2018)
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
S.Shota
March 17, 2018
Education
0
820
編入試験への準備と編入後の生活 (Ver.2018)
第6回関東合同編入説明会 (
https://www.zenpen-kosen.com/kantou_6/
) のフリートークで使用したスライドです
S.Shota
March 17, 2018
Tweet
Share
More Decks by S.Shota
See All by S.Shota
[ICLR/ICML2019読み会] Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
satuma777
2
3.3k
論文紹介:Neural Architecture Search with Bayesian Optimisation and Optimal Transport [Kandasamy et al., NIPS 2018]
satuma777
0
1.1k
Path-Level Network Transformation for Efficient Architecture Search (ICML2018読み会)
satuma777
5
1.3k
論文紹介:Efficient Architecture Search by Network Transformation [Cai et al., AAAI-2018]
satuma777
0
1.1k
新ラボ生向けチュートリアル:文献調査(サーベイ)の仕方
satuma777
0
1.2k
The beautiful world of evolutionary computation made by probability and statistics
satuma777
0
1.2k
論文紹介:Gradient Boosted Feature Selection
satuma777
0
1.1k
論文紹介:Neural Architecture Search with Reinforcement Learning
satuma777
0
1.7k
論文紹介:Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves
satuma777
0
1.2k
Other Decks in Education
See All in Education
TeXで変える教育現場
doratex
1
18k
Leveraging LLMs for student feedback in introductory data science courses (Stats Up AI)
minecr
1
230
高校数学とJulia言語
shimizudan
0
130
Introduction - Lecture 1 - Information Visualisation (4019538FNR)
signer
PRO
0
5.3k
2026 Medicare 101 Presentation
robinlee
PRO
0
170
Surviving the surfaceless web
jonoalderson
0
730
【dip】「なりたい自分」に近づくための、「自分と向き合う」小さな振り返り
dip_tech
PRO
0
260
令和エンジニアの学習法 〜 生成AIを使って挫折を回避する 〜
moriga_yuduru
0
270
Analysis and Validation - Lecture 4 - Information Visualisation (4019538FNR)
signer
PRO
0
2.5k
滑空スポーツ講習会2025(実技講習)EMFT学科講習資料/JSA EMFT 2025
jsaseminar
0
290
Avoin jakaminen ja Creative Commons -lisenssit
matleenalaakso
0
2.1k
2025年の本当に大事なAI動向まとめ
frievea
1
190
Featured
See All Featured
職位にかかわらず全員がリーダーシップを発揮するチーム作り / Building a team where everyone can demonstrate leadership regardless of position
madoxten
61
52k
Noah Learner - AI + Me: how we built a GSC Bulk Export data pipeline
techseoconnect
PRO
0
130
Building Experiences: Design Systems, User Experience, and Full Site Editing
marktimemedia
0
440
Avoiding the “Bad Training, Faster” Trap in the Age of AI
tmiket
0
97
Navigating the Design Leadership Dip - Product Design Week Design Leaders+ Conference 2024
apolaine
0
220
Testing 201, or: Great Expectations
jmmastey
46
8.1k
KATA
mclloyd
PRO
35
15k
Taking LLMs out of the black box: A practical guide to human-in-the-loop distillation
inesmontani
PRO
3
2.1k
Music & Morning Musume
bryan
47
7.1k
Become a Pro
speakerdeck
PRO
31
5.8k
SEO Brein meetup: CTRL+C is not how to scale international SEO
lindahogenes
0
2.4k
Documentation Writing (for coders)
carmenintech
77
5.3k
Transcript
ୈճؔ౦߹ಉฤೖઆ໌ձ!ίϩϓϥ ฤೖࢼݧͷ४උͱ ฤೖޙͷੜ׆ ੪౻ ᠳଡ ڥใֶ ใϝσΟΞڥֶઐ߈ ใϝσΟΞֶίʔε നݚڀࣨ म࢜
݄
"CPVU.F • ੪౻ ᠳଡ αΠτ γϣλ • BLBͭ͞·
TBUVNB • ɿ!EBZUC@UXZ • ɿTBUVNB • ϙʔτϑΥϦΦɾϒϩάɿ • IUUQTBUVNBQPSUGPMJPYZ[BCPVU • IUUQTBUVNBQPSUGPMJPIBUFCMPKQ
"CPVU.FɿֶྺαϚϦʔ • ɿἚߴઐ ిࢠใֶՊ ଔۀ • Ṳནঘݚڀࣨ ग़ɼଔݚςʔϚ"3 •
ɿԣࠃཱେֶ ཧֶ෦ ɾిࢠใܥֶՊ ใֶ&1ଔۀ • ݱࡏɿԣࠃཱେֶ ڥใֶ ใ ϝσΟΞڥֶઐ߈ ใϝσΟΞֶίʔε • നਅҰݚڀࣨ ॴଐɼݚڀςʔϚػցֶश
େֶબͼͷج४ • ୈҰʹ༏ઌ͖͢ʮݚڀࣨʯ • ͕ࣗΓ͍ͨݚڀԿʁ • ͦͷςʔϚʹ߹க͢Δݚڀࣨଘࡏ͢Δʁ • ࣌ؒతɾڑతɾۚમతʹ༨༟͕͋Ε
ݚڀࣨݟֶͷ͓ئ͍Λ͠Α͏ • େͷ1* 1SJODJQBM*OWFTUJHBUPSݚڀࣨओ࠻ շ͘ड͚ೖΕͯ͘ΕΔͣ • ΑΓςʔϚʹ߹கͨ͠ଞͷઌੜΛ հͯ͘͠ΕΔέʔε
ฤೖࢼݧͷରࡦ • ใֶ&1ͷ߹ɼࢼݧՊͭ • ֶʢඍੵɾઢܗʣɼཧʢྗֶʣɼ ઐՊʢཧճ࿏ $ݴޠ +BWBʣ •
ӳޠ50&*$ͷείΞΛఏग़ • աڈˠॻ੶ˠաڈͷॱʹऔΓΉ • աڈʮͷΈʯͨΓతͰඇৗʹةݥ • ͓͢͢Ίͷॻ੶ͪ͜Βʹ ·ͱΊ·ͨ͠ˠ https://www.slideshare.net/ShotaSatuma/ss-66615294
୯Ґৼସʹ͍ͭͯ • ిࢠใܥˠใܥͷΑ͏ʹҟͳΔઐ߈ʹ ҠΔͱৼସՄೳͳ୯Ґগͳ͘ͳΔ • ࢲͷ߹ɿߴઐࣗମʹऔಘͨ͠ిؾܥՊͷ ୯Ґ΄ͱΜͲৼସઌͳ͠ • Պམͱͨ͠Βཹͱ͍͏ͱ͜Ζ͔Β
ελʔτͱ͍͏έʔεʜ • ෦ੜΑΓ୯Ґ͕গͳΊͳͷͰɼ ߴઐ࣌ΑΓؤுΔඞཁ͋Γ
େֶͷߨٛ • ҰൠڭཆՊ͕໘ന͍ • ϕϯνϟʔ͔ΒֶͿϚωδϝϯτͳͲ • ઐجૅՊɿֶɾཧɾԽֶͷجૅ • ઢܗɼྗֶɼࡐྉ༗ػԽֶʜ
• ใֶ&1ͷઐՊ෯͍ • σʔλϕʔεɼใηΩϡϦςΟɼػցֶशɼ ܭࢉཧɼใࣾձྙཧɼཧݴޠֶʜ
ฤೖ͔Βͷڭһ໔ڐऔಘ • ใֶ&1ͰऔಘՄೳͳڭһ໔ڐɿ • தֶߍڭ་Ұछ໔ڐঢ়ʢֶɾཧՊʣ • ߴֶߍڭ་Ұछ໔ڐঢ়ʢֶɾཧՊɾใʣ • தֶߍ
ֶ ͱߴߍ ֶɾใ Λऔಘ • ͜ͷέʔεͰଔۀཁ݅୯Ґʴ୯Ґ • ҆қʹऔΖ͏ͱ͢Δͷ ͓͢͢Ί͠·ͤΜʜ
ฤೖ͔Βͷڭһ໔ڐऔಘ • ՃͰऔΔඞཁ͕͋ͬͨ୯Ґɿ • ڭ৬ؔ࿈ • ڭҭ৺ཧֶɼڭՊڭҭ๏ɼಓಙڭҭͳͲ • ڭՊؔ࿈
• ֶɼزԿֶɼใॲཧͳͲ • िؒͷհޢࢱࢪઃͰͷ࣮श • िؒͷڭҭ࣮श • ߴߍ໔ڐͳΒिؒɼதֶ໔ڐͳΒिؒ
εέδϡʔϧʢલظʣ ̍ݶ ̎ݶ ̏ݶ ̐ݶ ̑ݶ ̒ݶ ̓ݶ ʙ
ʙ ʙ ʙ ʙ ʙ ʙ ݄ ཧ ݴޠֶ" ใཧ ຊࠃ ݑ๏ ౷ܭֶ *$ Ր ιϑτΣΞ ֶ ϓϩδΣΫτ ϥʔχϯά ΞϧόΠτ ਫ ࡐྉ ༗ػԽֶ ཧɾԽֶ࣮ݧ ίϯύΠϥ ใ ηΩϡϦςΟ زԿֶ* ڭҭ૬ஊͷ جૅͱํ๏ ۚ ϚϧνϝσΟΞ ใॲཧ ใֶ ֓ தࠃޠ B ूதߨٛʢલظʣ ใՊڭҭ๏** தֶՊڭҭ๏** ڭ৬ ɿ௨ৗͷଔۀཁ݅ʹؔΘΔߨٛ ɿڭһ໔ڐऔಘʹؔΘΔߨٛ
εέδϡʔϧʢޙظʣ ̍ݶ ̎ݶ ̏ݶ ̐ݶ ̑ݶ ̒ݶ ̓ݶ ʙ
ʙ ʙ ʙ ʙ ʙ ʙ ݄ ڭҭͷ ৺ཧֶ σΟδλϧɾ ίϛϡχέʔγϣϯ ݱ࣏ ʢຊʣ ίϯϐϡʔλ γεςϜͱ ίϛϡχέʔ γϣϯ ౷ܭֶ **$ ΧϦΩϡϥϜ Ր ใࣾձ ྙཧ ը૾ɾԻ ใॲཧ தֶՊ ڭҭ๏* ϕϯνϟʔ͔Β ֶͿϚωδϝϯτ ڭҭ جૅ ਫ ࡐྉ ༗ػԽֶ ྗֶ ใֶ ಛผԋश ΞϧόΠτ ઢܗ ֶ** σʔλϕʔε ଟ༷ମ ಓಙڭҭͷ ཧͱํ๏ ۚ ࡐྉ ແػԽֶ ݱͷ ܦࡁ# ֬ Ϟσϧ தࠃޠ B ΞϧόΠτ ूதߨٛʢޙظʣ ڭҭํ๏ ɿ௨ৗͷଔۀཁ݅ʹؔΘΔߨٛ ɿڭһ໔ڐऔಘʹؔΘΔߨٛ
εέδϡʔϧʢલظʣ ̍ݶ ̎ݶ ̏ݶ ̐ݶ ̑ݶ ̒ݶ ̓ݶ ʙ
ʙ ʙ ʙ ʙ ʙ ʙ ݄ ڭҭܦӦ ΞϧόΠτ Ր ྠߨ ۀܦӦ ਫ ܭࢉཧ** ྠߨ తࡒ࢈ ΞϧόΠτ ۚ ྠߨ ֶ* ઌిࢠ ใֶ ࣭ཧ ूதߨٛʢલظʣ ڭҭࣾձֶ ੜెɾਐ࿏ࢦಋ ڭҭ࣮शࣄલࢦಋ ɿ௨ৗͷଔۀཁ݅ʹؔΘΔߨٛ ɿڭһ໔ڐऔಘʹؔΘΔߨٛ
εέδϡʔϧʢޙظʣ ̍ݶ ̎ݶ ̏ݶ ̐ݶ ̑ݶ ̒ݶ ̓ݶ ʙ
ʙ ʙ ʙ ʙ ʙ ʙ ݄ ྠߨ Ր ྠߨ ਫ ΞϧόΠτ ΞϧόΠτ ۚ ྠߨ ֬ɾ ౷ܭ ಛผ ׆ಈ ڭ৬࣮ઓ ԋश ूதߨٛʢޙظʣ ڭҭ࣮शࣄޙࢦಋ ڭҭ࣮श"ɾ# հޢࢱ࣮श ɿ௨ৗͷଔۀཁ݅ʹؔΘΔߨٛ ɿڭһ໔ڐऔಘʹؔΘΔߨٛ
ʑͷੜ׆ • ΞϧόΠτˍΠϯλʔϯγοϓ • क़ߨࢣͷΞϧόΠτʢिʙʣ • 8FCΤϯδχΞظΠϯλʔϯʢिʣ • ༡Ϳ༨༟࡞ΕΔ
• Πϕϯτ͍͍ͩͨͳͷͰʜ • ूதߨٛΛ͏·͘ආ͚ͯ ՆϑΣεߦͬͨΓʜ
େֶӃʹ͍ͭͯ • ฤೖੜͰਪનऔΕΔ • ڥใֶͷ߹ʮ্ҐʯPS ʮҎ্Ͱऔಘͨ͠୯Ґ͕Ҏ্ʯ • ߴઐ࣌ͷؔ͠ͳ͍ •
ߴઐ࣌ͷ୯Ґऔಘ࣌ͷʹؔͳ͘ ʮৼସ୯ҐʯͱΈͳ͞ΕΔͨΊ • Ӄਐ͔ब৬͔͙͢ʹબ͕ഭΒΕΔͷͰ େֶೖֶޙ͔Βߟ͑࢝ΊΔͷ͕͓͢͢Ί
࠷ޙʹɿฤೖͷ1304ʗ$0/4 • ฤೖͷ͍͍ͱ͜Ζʢ1304ʣ • ෯͍ڭཆɾઐՊΛਂΊΔ͜ͱ͕Մೳ • ىۀΛ͡Ίͱͯ͠νϟϯεࢸΔॴʹ • ฤೖͷѱ͍ͱ͜Ζʢ$0/4ʣ
• ߴઐ࣌ʹशͬͨ͜ͱΛ࠶श͏͜ͱʜ • ཹͷϦεΫߴΊ ʮେֶʯΛ͍ͤΔ͔ ࣗͷ৺͕͚࣍ୈ