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
NLP2019_report.pdf
Search
MARUYAMA
March 19, 2019
0
130
NLP2019_report.pdf
MARUYAMA
March 19, 2019
Tweet
Share
More Decks by MARUYAMA
See All by MARUYAMA
vampire.pdf
tmaru0204
0
180
Misspelling_Oblivious_Word_Embedding.pdf
tmaru0204
0
190
Simple_Unsupervised_Summarization_by_Contextual_Matching.pdf
tmaru0204
0
180
Controlling_Text_Complexity_in_Neural_Machine_Translation.pdf
tmaru0204
0
160
20191028_literature-review.pdf
tmaru0204
0
150
Hint-Based_Training_for_Non-Autoregressive_Machine_Translation.pdf
tmaru0204
0
140
Soft_Contextual_Data_Augmentation_for_Neural_Machine_Translation_.pdf
tmaru0204
0
160
An_Embarrassingly_Simple_Approach_for_Transfer_Learning_from_Pretrained_Language_Models_.pdf
tmaru0204
0
150
Addressing_Trobulesome_Words_in_Neural_Machine_Translation.pdf
tmaru0204
0
150
Featured
See All Featured
Build your cross-platform service in a week with App Engine
jlugia
231
18k
Agile that works and the tools we love
rasmusluckow
330
21k
The Power of CSS Pseudo Elements
geoffreycrofte
77
6k
The World Runs on Bad Software
bkeepers
PRO
70
11k
GitHub's CSS Performance
jonrohan
1032
460k
Documentation Writing (for coders)
carmenintech
74
5k
Writing Fast Ruby
sferik
628
62k
Optimizing for Happiness
mojombo
379
70k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
7
840
Making the Leap to Tech Lead
cromwellryan
135
9.5k
StorybookのUI Testing Handbookを読んだ
zakiyama
31
6.1k
Building a Modern Day E-commerce SEO Strategy
aleyda
43
7.6k
Transcript
ݴޠॲཧֶձ ୈճ࣍େձ ࢀՃใࠂ Ԭٕज़Պֶେֶɹؙࢁւ
ใࠂ༰ ⾣ ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ग़ྗ੍ޚΛߟྀͨ͠ݟग़͠ੜϞσϧͷͨΊͷ େنίʔύε ਓݟ༤ଠ, ాޱ༤࠸, ాल໌ (ே৽ฉ),
٠ాᔨ, ௗӋೋ (ϨτϦό), Ԭ࡚؍ (౦େ), ס݈ଠ (౦େ), Ԟଜֶ (౦େ) ੪౻͍ͭΈ, ాژհ, େ௩३࢙, ాޫำ, ઙٱࢠ, ా४ೋ (NTT)
ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ֓ཁ ɾΫΤϦͱग़ྗΛಉ࣌ʹߟྀͰ͖Δ౷ҰతͳϞσϧΛఏҊ ɾ༰બϞσϧ ੜϞσϧ ⾣ ߩݙ ɾ༰બϞσϧʹ͓͚ΔΫΤϦґଘɾඇґଘͷߟྀ ɾ༰બϞσϧʹ͓͚Δग़ྗͷ੍ޚ
ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ఏҊϞσϧ ɾ༰બϞσϧ ΫΤϦґଘҙػߏʹΑΓɺΫΤϦʹج͍ͮͨॏཁ୯ޠΛબ ΫΤϦඇґଘ୯ޠͷॏཁֶशύϥϝʔλʹؚΊΔ ग़ྗ੍ޚࢀরཁจͷFNCFEEJOHΛೖྗ
ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ఏҊϞσϧ ɾੜϞσϧ ༰બϞσϧʹΑΔ୯ޠͷॏΈ QPJOUFSHFOFSBUPSNPEFM ग़ྗ੍ޚଘ͞FNCFEEJOHΛೖྗ
ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ݁Ռ ɾग़ྗΛ͘͢Δͱɺࣝผˢɾ࠶ݱˣ ɾ͍จதʹΑΓॏཁͳใΛ٧ΊࠐΉ͜ͱ͕Ͱ͖͍ͯΔ
ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ݁Ռ
ग़ྗ੍ޚΛߟྀͨ͠ݟग़͠ੜϞσϧͷͨΊͷେنίʔύε ⾣ ֓ཁ ɾग़ྗ੍ޚϞσϧΛධՁ༻ίʔύεΛߏங ɾຊޠͷݟग़͠ੜͷͨΊͷֶश༻ίʔύεΛߏங +BQBOFTF.VMUJ-FOHUI)FBE-JOF$PSQVT +".6- +BQBOFTF/FXT$PSQVT +/$
ग़ྗ੍ޚΛߟྀͨ͠ݟग़͠ੜϞσϧͷͨΊͷେنίʔύε ⾣ ίʔύε
ग़ྗ੍ޚΛߟྀͨ͠ݟग़͠ੜϞσϧͷͨΊͷେنίʔύε ⾣ ίʔύε ɾ+".6- ࢴ໘ݟग़͠ ͓Αͼ จࣈͷ֤σδλϧݟग़͠ ݄d݄ͷؒʹ৴͞Εͨهࣄ
݅ ɾ+/$ dͷؒʹ৴͞Εͨهࣄ ࢴ໘ݟग़͠ ݅ IUUQXXXBTBIJDPNTIJNCVONFEJBMBC+".6- ແঈ IUUQXXXBTBIJDPNTIJNCVONFEJBMBC+/$ ༗ঈ
ใࠂ༰ ⾣ ΫΤϦɾग़ྗΛߟྀՄೳͳจॻཁϞσϧ ⾣ ग़ྗ੍ޚΛߟྀͨ͠ݟग़͠ੜϞσϧͷͨΊͷ େنίʔύε ਓݟ༤ଠ, ాޱ༤࠸, ాल໌ (ே৽ฉ),
٠ాᔨ, ௗӋೋ (ϨτϦό), Ԭ࡚؍ (౦େ), ס݈ଠ (౦େ), Ԟଜֶ (౦େ) ੪౻͍ͭΈ, ాژհ, େ௩३࢙, ాޫำ, ઙٱࢠ, ా४ೋ (NTT)