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Understand Functionality and Dimensionality of Vector Embeddings: the
  Distributional Hypothesis, the Pairwise Inner Product Loss and Its
  Bias-Variance Trade-off
v1v2v3v4 (latest)

Understand Functionality and Dimensionality of Vector Embeddings: the Distributional Hypothesis, the Pairwise Inner Product Loss and Its Bias-Variance Trade-off

1 March 2018
Zi Yin
ArXiv (abs)PDFHTML

Papers citing "Understand Functionality and Dimensionality of Vector Embeddings: the Distributional Hypothesis, the Pairwise Inner Product Loss and Its Bias-Variance Trade-off"

7 / 7 papers shown
Title
Searching for Carriers of the Diffuse Interstellar Bands Across
  Disciplines, using Natural Language Processing
Searching for Carriers of the Diffuse Interstellar Bands Across Disciplines, using Natural Language Processing
Corentin van den Broek Dobrenan
F. Galliano
J. Minton
V. Botev
R. Wu
65
3
0
15 Nov 2022
DeepProphet2 -- A Deep Learning Gene Recommendation Engine
DeepProphet2 -- A Deep Learning Gene Recommendation Engine
Daniel Brambilla
Davide Giacomini
Luca Muscarnera
Andrea Mazzoleni
78
1
0
03 Aug 2022
Effects of Number of Filters of Convolutional Layers on Speech
  Recognition Model Accuracy
Effects of Number of Filters of Convolutional Layers on Speech Recognition Model Accuracy
James Mou
Jun Li
39
3
0
03 Feb 2021
Word Embeddings: Stability and Semantic Change
Word Embeddings: Stability and Semantic Change
Lucas Rettenmeier
BDL
41
1
0
23 Jul 2020
weg2vec: Event embedding for temporal networks
weg2vec: Event embedding for temporal networks
M. Torricelli
M. Karsai
L. Gauvin
AI4TS
60
30
0
06 Nov 2019
The Global Anchor Method for Quantifying Linguistic Shifts and Domain
  Adaptation
The Global Anchor Method for Quantifying Linguistic Shifts and Domain Adaptation
Zi Yin
Vin Sachidananda
B. Prabhakar
36
24
0
12 Dec 2018
On the Dimensionality of Word Embedding
On the Dimensionality of Word Embedding
Zi Yin
Yuanyuan Shen
83
193
0
11 Dec 2018
1