Home
Catalogue search
Refine your search:
Keyword
Creator / Publisher:
Bollegala, Danushka (13)
Hakami, Huda (3)
Kaneko, Masahiro (3)
Bel, Núria (2)
Coenen, Frans (2)
Goulermas, Yannis (2)
Mandya, Angrosh (2)
Scott, Donia (2)
The 28th International Conference on Computational Linguistics 2020 (2)
Zong, Chengqing (2)
more
Year:
2020 (13)
Medium
Type
BLLDB-Access
Search in the Catalogues and Directories
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
Sort by
creator [A → Z]
'
creator [Z → A]
'
publishing year ↑ (asc)
'
publishing year ↓ (desc)
'
title [A → Z]
'
title [Z → A]
'
Simple Search
Hits 1 – 13 of 13
1
Autoencoding Improves Pre-trained Word Embeddings ...
Kaneko, Masahiro
;
Bollegala, Danushka
. - : arXiv, 2020
Abstract:
Prior work investigating the geometry of pre-trained word embeddings have shown that word embeddings to be distributed in a narrow cone and by centering and projecting using principal component vectors one can increase the accuracy of a given set of pre-trained word embeddings. However, theoretically, this post-processing step is equivalent to applying a linear autoencoder to minimise the squared l2 reconstruction error. This result contradicts prior work (Mu and Viswanath, 2018) that proposed to remove the top principal components from pre-trained embeddings. We experimentally verify our theoretical claims and show that retaining the top principal components is indeed useful for improving pre-trained word embeddings, without requiring access to additional linguistic resources or labelled data. ... : COLING 2020 ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://dx.doi.org/10.48550/arxiv.2010.13094
https://arxiv.org/abs/2010.13094
BASE
Hide details
2
Autoencoding Improves Pre-trained Word Embeddings ...
The 28th International Conference on Computational Linguistics 2020
;
Bollegala, Danushka
;
Kaneko, Masahiro
. - : Underline Science Inc., 2020
BASE
Show details
3
Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction ...
The 28th International Conference on Computational Linguistics 2020
;
Bollegala, Danushka
;
Coenen, Frans
. - : Underline Science Inc., 2020
BASE
Show details
4
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction ...
Bollegala, Danushka
;
Kiryo, Ryuichi
;
Tsujino, Kosuke
. - : arXiv, 2020
BASE
Show details
5
Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction.
Mandya, Angrosh
;
Coenen, Frans
;
Bollegala, Danushka
. - : International Committee on Computational Linguistics, 2020
BASE
Show details
6
Multi-Source Attention for Unsupervised Domain Adaptation.
Bollegala, Danushka
;
Cui, Xia
. - : Association for Computational Linguistics, 2020
BASE
Show details
7
Learning to Compose Relational Embeddings in Knowledge Graphs
Hakami, Huda
;
Chen, Wenye
;
Bollegala, Danushka
. - : Springer Singapore, 2020
BASE
Show details
8
Tree-Structured Neural Topic Model
Isonuma, Masaru
;
Mori, Junichiro
;
Bollegala, Danushka
. - 2020
BASE
Show details
9
A Pilot Study on Argument Simplification in Stance-Based Opinions
Bollegala, Danushka
;
Rajendran, Pavithra
;
Parsons, Simon
. - : Springer Singapore, 2020
BASE
Show details
10
Joint Approaches for Learning Word Representations from Text Corpora and Knowledge Bases
Alsuhaibani, Mohammed
. - 2020
BASE
Show details
11
Autoencoding Improves Pre-trained Word Embeddings.
Kaneko, Masahiro
;
Bollegala, Danushka
. - : International Committee on Computational Linguistics, 2020
BASE
Show details
12
Context-Guided Self-supervised Relation Embeddings
Hakami, Huda
;
Bollegala, Danushka
. - : Springer Singapore, 2020
BASE
Show details
13
A Study on Learning Representations for Relations Between Words
Hakami, Huda
. - 2020
BASE
Show details
Mobile view
All
Catalogues
UB Frankfurt Linguistik
0
IDS Mannheim
0
OLC Linguistik
0
UB Frankfurt Retrokatalog
0
DNB Subject Category Language
0
Institut für Empirische Sprachwissenschaft
0
Leibniz-Centre General Linguistics (ZAS)
0
Bibliographies
BLLDB
0
BDSL
0
IDS Bibliografie zur deutschen Grammatik
0
IDS Bibliografie zur Gesprächsforschung
0
IDS Konnektoren im Deutschen
0
IDS Präpositionen im Deutschen
0
IDS OBELEX meta
0
MPI-SHH Linguistics Collection
0
MPI for Psycholinguistics
0
Linked Open Data catalogues
Annohub
0
Online resources
Link directory
0
Journal directory
0
Database directory
0
Dictionary directory
0
Open access documents
BASE
13
Linguistik-Repository
0
IDS Publikationsserver
0
Online dissertations
0
Language Description Heritage
0
© 2013 - 2024 Lin|gu|is|tik
|
Imprint
|
Privacy Policy
|
Datenschutzeinstellungen ändern