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_...
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
MARUYAMA
July 10, 2019
0
160
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
190
Misspelling_Oblivious_Word_Embedding.pdf
tmaru0204
0
210
Simple_Unsupervised_Summarization_by_Contextual_Matching.pdf
tmaru0204
0
190
Controlling_Text_Complexity_in_Neural_Machine_Translation.pdf
tmaru0204
0
180
20191028_literature-review.pdf
tmaru0204
0
160
Hint-Based_Training_for_Non-Autoregressive_Machine_Translation.pdf
tmaru0204
0
150
Soft_Contextual_Data_Augmentation_for_Neural_Machine_Translation_.pdf
tmaru0204
0
180
Addressing_Trobulesome_Words_in_Neural_Machine_Translation.pdf
tmaru0204
0
180
Simple_Unsupervised_Keyphrase_Extraction_using_Sentence_Embeddings.pdf
tmaru0204
0
200
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
59
50k
[SF Ruby Conf 2025] Rails X
palkan
2
810
Site-Speed That Sticks
csswizardry
13
1.1k
HDC tutorial
michielstock
1
490
Art, The Web, and Tiny UX
lynnandtonic
304
21k
Claude Code どこまでも/ Claude Code Everywhere
nwiizo
63
53k
Ethics towards AI in product and experience design
skipperchong
2
210
VelocityConf: Rendering Performance Case Studies
addyosmani
333
24k
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
32
2.3k
Impact Scores and Hybrid Strategies: The future of link building
tamaranovitovic
0
220
GraphQLの誤解/rethinking-graphql
sonatard
75
11k
Mobile First: as difficult as doing things right
swwweet
225
10k
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