$30 off During Our Annual Pro Sale. View Details »
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Soft_Contextual_Data_Augmentation_for_Neural_Ma...
Search
MARUYAMA
August 25, 2019
0
170
Soft_Contextual_Data_Augmentation_for_Neural_Machine_Translation_.pdf
MARUYAMA
August 25, 2019
Tweet
Share
More Decks by MARUYAMA
See All by MARUYAMA
vampire.pdf
tmaru0204
0
190
Misspelling_Oblivious_Word_Embedding.pdf
tmaru0204
0
200
Simple_Unsupervised_Summarization_by_Contextual_Matching.pdf
tmaru0204
0
190
Controlling_Text_Complexity_in_Neural_Machine_Translation.pdf
tmaru0204
0
170
20191028_literature-review.pdf
tmaru0204
0
160
Hint-Based_Training_for_Non-Autoregressive_Machine_Translation.pdf
tmaru0204
0
150
An_Embarrassingly_Simple_Approach_for_Transfer_Learning_from_Pretrained_Language_Models_.pdf
tmaru0204
0
160
Addressing_Trobulesome_Words_in_Neural_Machine_Translation.pdf
tmaru0204
0
170
Simple_Unsupervised_Keyphrase_Extraction_using_Sentence_Embeddings.pdf
tmaru0204
0
190
Featured
See All Featured
The Hidden Cost of Media on the Web [PixelPalooza 2025]
tammyeverts
1
93
Cheating the UX When There Is Nothing More to Optimize - PixelPioneers
stephaniewalter
285
14k
How to train your dragon (web standard)
notwaldorf
97
6.4k
How to Ace a Technical Interview
jacobian
280
24k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
367
27k
The Illustrated Children's Guide to Kubernetes
chrisshort
51
51k
CoffeeScript is Beautiful & I Never Want to Write Plain JavaScript Again
sstephenson
162
15k
[RailsConf 2023 Opening Keynote] The Magic of Rails
eileencodes
31
9.8k
Automating Front-end Workflow
addyosmani
1371
200k
Building Applications with DynamoDB
mza
96
6.8k
Being A Developer After 40
akosma
91
590k
RailsConf 2023
tenderlove
30
1.3k
Transcript
4PGU$POUFYUVBM%BUB"VHNFOUBUJPO GPS/FVSBM.BDIJOF5SBOTMBUJPO 'FJ(BP +JOIVB;IV -JKVO8V :JOHDF9JB 5BP2JO 9VFRJ$IFOH 8FOHBOH;IPV 5JF:BO-JV
"$- QBHFTr -JUFSBUVSFSFWJFX /BHBPLB6OJWFSTJUZPG5FDIOPMPHZ5BLVNJ.BSVZBNB
"CTUSBDU ⾣จ຺Λߟྀͨ͠ιϑτͳσʔλ֦ு ⾣χϡʔϥϧػց༁ʹ͓͚Δσʔλ֦ுख๏ΛఏҊ ⾣σʔλ͕গͳ͍߹ɾେྔʹ͋Δ߹ɺͲͪΒʹ͓͍ͯ طଘͷσʔλ֦ுख๏Λ্ճΔੑೳΛୡ
.FUIPE ⾣4PGUDPOUFYUVBMEBUBBVHNFOUBUJPO ɾFNCFEEJOHPGTPGUXPSEТ EFNCFEEJOHNBUSJY
&YQFSJNFOU ⾣#BTFMJOFT #BTFσʔλ֦ுख๏ෆ༻ 4XBQ૭෯LͷதͰɺϥϯμϜʹ୯ޠͷҐஔΛೖΕସ͑ %SPQPVUϥϯμϜʹ୯ޠΛܽམ
&YQFSJNFOU ⾣#BTFMJOFT #MBOLϥϯμϜʹQMBDFIPMEFSUPLFOl@zʹஔ͖͑ 4NPPUIVOJHSBNͷසʹج͍ͮͯ୯ޠΛαϯϓϦϯά͠ɺ -.TBNQMF ݴޠϞσϧͷग़ྗʹج͍ͮͯ୯ޠΛαϯϓϦϯά͠ɺ ϥϯμϜʹஔ͖͑ ϥϯμϜʹஔ͖͑
&YQFSJNFOU ⾣%BUBTFUT ɾ*845\(FSNBO 4QBOJTI )FCSFX^ˠ&OHMJTI ɾ8.5&OHMJTIˠ(FSNBO ⾣.PEFM ɾ-. /.5USBOTGPSNFSBSDIJUFDUVSF ɾSFQMBDJOHQSPCBCJMJUZЍ\
^
&YQFSJNFOU
&YQFSJNFOU ఏҊख๏ЍͰɺ #-&6͕࠷େ طଘख๏ЍͰɺ #-&6Լ
$PODMVTJPOT ⾣จ຺Λߟྀͨ͠ιϑτͳσʔλ֦ு ⾣χϡʔϥϧػց༁ʹ͓͚Δσʔλ֦ுख๏ΛఏҊ ⾣σʔλ͕গͳ͍߹ɾେྔʹ͋Δ߹ɺͲͪΒʹ͓͍ͯ طଘͷσʔλ֦ுख๏Λ্ճΔੑೳΛୡ