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
論文紹介 Hardness-Aware Deep Metric Learning [CVPR ...
Search
hyodo
June 10, 2019
Technology
560
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
論文紹介 Hardness-Aware Deep Metric Learning [CVPR 2019]
研究室のゼミで"Deep Metric Learning"というタイトルで発表した資料の一部になります。ご指摘や議論等お待ちしております。
Twitter @onysuke
hyodo
June 10, 2019
More Decks by hyodo
See All by hyodo
The Impact of Advertising along the Conversion Funnel
onysuke
2
1.8k
Can offline stores drive online sales?
onysuke
0
1.7k
SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce
onysuke
0
1k
意思決定のための機械学習
onysuke
1
1.1k
Mixture of Expertsに関する文献調査
onysuke
1
2.2k
Other Decks in Technology
See All in Technology
カートの信頼性を担保するWireMockを使ったe2eテスト
ykagano
0
600
【書籍出版記念】 10周回って、エージェント開発は RAGがすべてだった。〜RAGの歴史と開発現場で見えた実践知〜
akiratameto
2
380
属人化を叩き割れ!「制作加速」と「安定化」の矛盾を打破する:8年目プロダクトが辿り着いた「ミスが起こり得ない」アセット制作フローの全貌
gree_tech
PRO
0
110
20260817_生成AIの動向と中学校・高等学校での活用を考える_v1.00_公開用
doradora09
PRO
0
110
【GCC2026】TrueHDRIを用いたルックデブ環境とライティングテクニック
bandainamcostudios
PRO
0
120
Bits Agent Builder の⼊⾨と活⽤事例
nulabinc
PRO
0
250
Genie Codeハンズオン応用編
taka_aki
0
130
【AG-UI × A2UI × MCP Apps】Generative UIをやさしく解説する
nrinetcom
PRO
1
150
LLM Internals: 언어 모델의 계보와 알고리즘 진화 (2023~2026)
inureyes
PRO
1
790
MIXIで活躍できるエンジニアを 若手社員目線で考えてみる
mixi_engineers
PRO
0
100
生成 AI の基礎 〜 サンプル実装で学ぶ基本原理
enakai00
7
4.5k
形式手法特論:Hyperproperty とモデル検査 #kernelvm / Kernel VM Study Tokyo 19th
ytaka23
0
130
Featured
See All Featured
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
32
4.4k
Scaling GitHub
holman
464
140k
Noah Learner - AI + Me: how we built a GSC Bulk Export data pipeline
techseoconnect
PRO
0
390
The browser strikes back
jonoalderson
0
1.5k
Mobile First: as difficult as doing things right
swwweet
225
10k
Have SEOs Ruined the Internet? - User Awareness of SEO in 2025
akashhashmi
0
430
End of SEO as We Know It (SMX Advanced Version)
ipullrank
3
4.4k
The B2B funnel & how to create a winning content strategy
katarinadahlin
PRO
1
470
Kristin Tynski - Automating Marketing Tasks With AI
techseoconnect
PRO
0
470
エンジニアに許された特別な時間の終わり
watany
108
250k
Agile Actions for Facilitating Distributed Teams - ADO2019
mkilby
0
260
Mind Mapping
helmedeiros
PRO
1
320
Transcript
)BSEOFTT"XBSF%FFQ.FUSJD-FBSOJOH $7130SBM 8FO[IBP ;IFOH ;IBPEPOH $IFO +JXFO -V +JF ;IPV
%FQBSUNFOUPG"VUPNBUJPO 5TJOHIVB6OJWFSTJUZ $IJOB FUD 1
֓ཁ 2 ɾ/FHBUJWFTBNQMFͷқΛௐ͢ΔϑϨʔϜϫʔΫ )%.- )BSEOFTT"XBSF%FFQ.FUSJD-FBSOJOH ΛఏҊ /FHBUJWFTBNQMFͷқΛજࡏ্ۭؒͷઢܗิؒʹΑΓௐ ֶशঢ়گʹదͳ͠͞ͷOFHBUJWFαϯϓϧΛੜ͢Δ
എܠ • /FHBUJWFTBNQMJOHॏཁͳ • ఏҊ͞Ε͍ͯΔख๏ͷଟ͘ɼֶशΛଅਐ͢Δ ͠ ͍ /FHBUJWFΛͲ͏બ͢Δ͔ʹযΛ͍͋ͯͯͨ ‑ Ұ෦ͷTBNQMFΛऔΓଓ͚Δ͜ͱʹͳΓɼજࡏۭؒͷେ
ہతͳܗΛଊ͑Δ͜ͱ͕Ͱ͖͍ͯͳ͍ PWFSGJUUJOH 3
4 ఏҊख๏֓આ ᶃ )BSEBXBSFGFBUVSFTZOUIFTJT ΞϯΧʔʹ͚ۙͮͨOFHBUJWF ! Λੜ ᶄ )BSEOFTTBOE-BCFM1SFTFSWJOHGFBUVSFTZOUIFTJT
ੜͨ͠OFHBUJWF ! Λ ͷϥϕϧͱಉ͡ʹͳΔΑ͏ʹඍௐ ᶃ ᶄ ! " = "
5 .BOJGPME $MBTT" ఏҊख๏֓આ ᶃ)BSEBXBSFGFBUVSFTZOUIFTJT .BOJGPME $MBTT#
6 .BOJGPME $MBTT" : → GFBUVSFTQBDF͔Β FNCFEEJOHTQBDF NFUSJDTQBDF ʹࣹӨ ఏҊख๏֓આ
ᶃ)BSEBXBSFGFBUVSFTZOUIFTJT .BOJGPME $MBTT#
7 .BOJGPME $MBTT" & ! = + " ! −
" ∈ [0,1] ҎԼͷઢܗิؒʹΑΓ ʹ͚ۙͮͨΑΓ͍͠ ̂ Λੜ ఏҊख๏֓આ ᶃ)BSEBXBSFGFBUVSFTZOUIFTJT .BOJGPME $MBTT#
8 Hard-aware feature .BOJGPME $MBTT" l% !ͱ!͕ಉϥϕϧz อূ͞Ε͍ͯͳ͍ ˣ !ͱಉϥϕϧʹ
ͳΔΑ͏ͳ( !ΛϚοϓ ఏҊख๏֓આ ᶄ)BSEOFTTBOE-BCFM1SFTFSWJOHGFBUVSFTZOUIFTJT : → .BOJGPME $MBTT#
ఏҊϑϨʔϜϫʔΫ )%.- 9 : → : → .FUSJDOFUXPSL "VHNFOUFS HLP(Hardness-and-Label-Preserving)
Generator Network "VHNFOUFS )-1(FOFSBUPS/FUXPSL
"VHNFOUFS 10 : → : → .FUSJDOFUXPSL "VHNFOUPS & !
= + " ! − , "∈ 0,1 … (1) " = + + 1 − # , ! , , ! > # 1 , , ! ≤ # , ∈ 0,1 … (2) ; " ∈ $! $ ," , 1 ͱͯ͠ , ! = ! − ' % ! = + [ , ! + 1 − #] "! $ ," , , ! > # … (3) ' ! = * + [ ! " #!"# , ! + 1 − ! " #!"# $] ! − , ! , , ! > $ ! , , ! ≤ $ … (4) % = 0ͷͱ͖' ! = ͱͳͬͯ͠·͏ʜ ʹ Λೖ͢Δͱ = ! # $%&'ͱͯ͠
"VHNFOUFSֶशঢ়گʹԠͨ͡қͷOFHBUJWFΛੜ ; % # = ' + [ # $
%&'( , # + 1 − # $ %&'( &] # − , # , , # > & # , , # ≤ & … (4) '() ʜͭલͷFQPDIͷ"WFSBHFNFUSJDMPTT FY5SJQMFUMPTT 11 @AB খ େ # $ %&'( 0 1 % ! = + $! $ ," (! − ) % ! = ! % !ͷқ easy hard MPTTͷେ͖͞ ֶशঢ়گ ʹԠͯ͡ੜ͢ΔOFHBUJWFͷқΛௐ
)-1(FOFSBUPS/FUXPSL 12 : → : → "VHNFOUPS HLP(Hardness-and-Label-Preserving) Generator Network
9:; = <:=>; + λ?>@A = − B C + λ?>@A () , ) l% #ͱ#͕ಉϥϕϧzอূ͞Ε͍ͯͳ͍ ⇒ #ͱಉϥϕϧʹͳΔΑ͏ͳE #ΛϚοϓ HFOFSBUPS: → PCKFDUJWFGVODUJPO )-1(FOFSBUPS /FUXPSL &OD %FD ͱͯ͠ͷ੍߲ ݩͷϥϕϧ Λอূ͢Δ
.FUSJDOFUXPSL PCKFDUJWFGVODUJPO .FUSJDOFUXPSL 13 : → : → .FUSJDOFUXPSL "VHNFOUFS
HLP(Hardness-and-Label-Preserving) Generator Network EFGHIJ = ! K L!"#E + 1 − ! K L!"# MNO = ! K L!"#() + 1 − ! K L!"# (; ) NFUSJDMPTT FY5SJQMFUMPTT /QBJSMPTT ݩͷσʔλର ੜͨ͠σʔλର ৴པͰ͖Δ 㱺 ੜͨ͠σʔλର ৴པͰ͖ͳ͍ 㱺 ݩͷσʔλର HFOFSBUPS ͕ ͷNFUSJDMPTTʹॏ͖Λ͓͘
$6#σʔληοτ ௗͷը૾ छྨ ܭ ຕ 5SBJO ຕ छྨ 5FTU
ຕ छྨ 5SBJOͱ5FTUʹಉ͡Ϋϥεͷը૾ଘࡏ͠ͳ͍ 㱺 ;FSPTIPUTFUUJOH 14
࣮ݧઃఆ DMVTUFSJOHSFUSJFWBMUBTL 15 $MVTUFSJOHUBTL ධՁࢦඪ /.* ਖ਼نԽ૬ޓใྔ ' 3FDBMM!, 5FTU
5SBJO Clustering task Retrieval task 3FUSJFWBMUBTL ֤UFTUը૾ RVFSZ ʹରͯ͠ ,ίۙͷΛநग़͠ɼ ಉ͡Ϋϥε͕ଐ͍ͯ͠Ε TDPSFFMTFTDPSF
.FUSJDMPTTͷछྨʹΑΒͣ )%.-Ͱࣝผతͳಛྔ͕ಘΒΕͨ 16
!"#$ ֶ͕शʹ͓͍ͯॏཁͳཁૉͰ͋Δ 17 HFJQO ͳ͠ͰϕʔεϥΠϯΛ্ճΔ 㱺 *+,- ͚ͩͰݱ࣮తͳಛදݱͷϚοϐϯά͕ՄೳͰ͋ͬͨͱߟ͑ΒΕΔ
ΫϥεͷมԽ എܠ ࢹ র໌ FUD ΫϥεؒͷΘ͔ͣͳҧ͍ ௗͷ༷ 18 ʹରॲ