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
An_Embarrassingly_Simple_Approach_for_Transfer_Learning_from_Pretrained_Language_Models_.pdf
Search
MARUYAMA
July 10, 2019
0
110
An_Embarrassingly_Simple_Approach_for_Transfer_Learning_from_Pretrained_Language_Models_.pdf
MARUYAMA
July 10, 2019
Tweet
Share
More Decks by MARUYAMA
See All by MARUYAMA
vampire.pdf
tmaru0204
0
130
Misspelling_Oblivious_Word_Embedding.pdf
tmaru0204
0
130
Simple_Unsupervised_Summarization_by_Contextual_Matching.pdf
tmaru0204
0
130
Controlling_Text_Complexity_in_Neural_Machine_Translation.pdf
tmaru0204
0
120
20191028_literature-review.pdf
tmaru0204
0
120
Hint-Based_Training_for_Non-Autoregressive_Machine_Translation.pdf
tmaru0204
0
100
Soft_Contextual_Data_Augmentation_for_Neural_Machine_Translation_.pdf
tmaru0204
0
120
Addressing_Trobulesome_Words_in_Neural_Machine_Translation.pdf
tmaru0204
0
110
Simple_Unsupervised_Keyphrase_Extraction_using_Sentence_Embeddings.pdf
tmaru0204
0
160
Featured
See All Featured
Scaling GitHub
holman
457
140k
Distributed Sagas: A Protocol for Coordinating Microservices
caitiem20
322
20k
Bash Introduction
62gerente
604
210k
Mobile First: as difficult as doing things right
swwweet
216
8.6k
Building a Modern Day E-commerce SEO Strategy
aleyda
17
6.4k
Navigating Team Friction
lara
178
13k
In The Pink: A Labor of Love
frogandcode
138
21k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
659
120k
The Cost Of JavaScript in 2023
addyosmani
16
3.9k
The Cult of Friendly URLs
andyhume
74
5.7k
Git: the NoSQL Database
bkeepers
PRO
422
63k
RailsConf 2023
tenderlove
4
540
Transcript
"O&NCBSSBTTJOHMZ4JNQMF"QQSPBDIGPS 5SBOTGFS-FBSOJOHGSPN1SFUSBJOFE-BOHVBHF.PEFMT "MFYBOESB$ISPOPQPVMPV $ISJTUPT#B[JPUJT "MFYBOESPT1PUBNJBOPT /""$-)-5 QBHFTr -JUFSBUVSFSFWJFX /BHBPLB6OJWFSTJUZPG5FDIOPMPHZ5BLVNJ.BSVZBNB
"CTUSBDU ⾣FOEUPFOEʹֶशͤ͞ΔγϯϓϧͳసҠֶशख๏ΛఏҊ ⾣ࣄલֶशͨ͠ݴޠϞσϧΛྨλεΫʹpOFUVOJOH ⾣༷ʑͳςΩετྨλεΫͰɺطଘख๏Λ͑ΔੑೳΛୡ
3FMBUFEXPSL ⾣6-.'J5 %JTDSJNJOBUJWFpOFUVOJOH֤ͰֶशΛมԽͤ͞Δ 4MBOUFEUSJBOHVMBSMFBSOJOHSBUFT
.PEFM 4J"5- ⾣-.1SFUSBJOJOH ⾣5SBOTGFSBVYJMJBSZMPTT ɾFYQPOFOUJBMEFDBZPGЍ FQPDIຖʹЍΛࢦతʹݮਰ ɾTFRVFOUJBMVOGSFF[JOH ্ͷ͔Βॱ࣍ղౚ͠ɺpOFUVOJOH
&YQFSJNFOUBMTFUVQT ⾣%BUBTFUT ɾ*SPOZJSPOZEFUFDUJPO ɾ4FOUTFOUJNFOUBOBMZTJT ɾ4$W 4$WTBSDBTNEFUFDUJPO ɾ1TZDI&YQFNPUJPOSFDPHOJUJPO
3FTVMUT ⾣"CMBUJPOTUVEZ
3FTVMUT ⾣/VNCFSPGFYBNQMFT ɾ4J"5- DPOUJOVPVTMJOFT ɾ6-.'J5 EBTIFEMJOFT dσʔλఔͰɺ 6-.'J5ʹඖఢ͢Δੑೳ
3FTVMUT ⾣&YQPOFOUJBMEFDBZPGЍ *OJUJBMWBMVF 'JOBMWBMVF
$PODMVTJPO ⾣FOEUPFOEʹֶशͤ͞ΔγϯϓϧͳసҠֶशख๏ΛఏҊ ⾣ࣄલֶशͨ͠ݴޠϞσϧΛྨλεΫʹpOFUVOJOH ⾣༷ʑͳςΩετྨλεΫͰɺطଘख๏Λ͑ΔੑೳΛୡ