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Few-shot Learning for Topic Modeling

Few-shot Learning for Topic Modeling

19 April 2021
Tomoharu Iwata
    BDL
ArXivPDFHTML

Papers citing "Few-shot Learning for Topic Modeling"

30 / 30 papers shown
Title
Neural Topic Modeling with Continual Lifelong Learning
Neural Topic Modeling with Continual Lifelong Learning
Pankaj Gupta
Yatin Chaudhary
Thomas Runkler
Hinrich Schütze
BDL
CLL
45
49
0
19 Jun 2020
MetaFun: Meta-Learning with Iterative Functional Updates
MetaFun: Meta-Learning with Iterative Functional Updates
Jin Xu
Jean-François Ton
Hyunjik Kim
Adam R. Kosiorek
Yee Whye Teh
65
68
0
05 Dec 2019
Meta-Learning for Few-Shot Time Series Classification
Meta-Learning for Few-Shot Time Series Classification
Jyoti Narwariya
Pankaj Malhotra
Lovekesh Vig
Gautam M. Shroff
T. Vishnu
105
59
0
13 Sep 2019
Meta Learning with Relational Information for Short Sequences
Meta Learning with Relational Information for Short Sequences
Yujia Xie
Haoming Jiang
Feng Liu
T. Zhao
H. Zha
49
14
0
04 Sep 2019
Compositional generalization through meta sequence-to-sequence learning
Compositional generalization through meta sequence-to-sequence learning
Brenden M. Lake
CoGe
80
199
0
12 Jun 2019
Hierarchically Structured Meta-learning
Hierarchically Structured Meta-learning
Huaxiu Yao
Ying Wei
Junzhou Huang
Z. Li
60
203
0
13 May 2019
Episodic Training for Domain Generalization
Episodic Training for Domain Generalization
Da Li
Jianshu Zhang
Yongxin Yang
Cong Liu
Yi-Zhe Song
Timothy M. Hospedales
OOD
101
448
0
31 Jan 2019
Attentive Neural Processes
Attentive Neural Processes
Hyunjik Kim
A. Mnih
Jonathan Richard Schwarz
M. Garnelo
S. M. Ali Eslami
Dan Rosenbaum
Oriol Vinyals
Yee Whye Teh
88
441
0
17 Jan 2019
Unsupervised Learning via Meta-Learning
Unsupervised Learning via Meta-Learning
Kyle Hsu
Sergey Levine
Chelsea Finn
SSL
OffRL
75
230
0
04 Oct 2018
The Variational Homoencoder: Learning to learn high capacity generative
  models from few examples
The Variational Homoencoder: Learning to learn high capacity generative models from few examples
Luke B. Hewitt
Maxwell Nye
Andreea Gane
Tommi Jaakkola
J. Tenenbaum
BDL
DRL
GAN
81
68
0
24 Jul 2018
Meta-Learning with Latent Embedding Optimization
Meta-Learning with Latent Embedding Optimization
Andrei A. Rusu
Dushyant Rao
Jakub Sygnowski
Oriol Vinyals
Razvan Pascanu
Simon Osindero
R. Hadsell
132
1,370
0
16 Jul 2018
Conditional Neural Processes
Conditional Neural Processes
M. Garnelo
Dan Rosenbaum
Chris J. Maddison
Tiago Ramalho
D. Saxton
Murray Shanahan
Yee Whye Teh
Danilo Jimenez Rezende
S. M. Ali Eslami
UQCV
BDL
85
701
0
04 Jul 2018
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
277
501
0
11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
258
670
0
07 Jun 2018
Meta-learning with differentiable closed-form solvers
Meta-learning with differentiable closed-form solvers
Luca Bertinetto
João F. Henriques
Philip Torr
Andrea Vedaldi
ODL
82
930
0
21 May 2018
Few-shot Autoregressive Density Estimation: Towards Learning to Learn
  Distributions
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions
Scott E. Reed
Yutian Chen
T. Paine
Aaron van den Oord
S. M. Ali Eslami
Danilo Jimenez Rezende
Oriol Vinyals
Nando de Freitas
87
88
0
27 Oct 2017
Variational Memory Addressing in Generative Models
Variational Memory Addressing in Generative Models
J. Bornschein
A. Mnih
Daniel Zoran
Danilo Jimenez Rezende
BDL
53
63
0
21 Sep 2017
Meta-SGD: Learning to Learn Quickly for Few-Shot Learning
Meta-SGD: Learning to Learn Quickly for Few-Shot Learning
Zhenguo Li
Fengwei Zhou
Fei Chen
Hang Li
92
1,118
0
31 Jul 2017
Prototypical Networks for Few-shot Learning
Prototypical Networks for Few-shot Learning
Jake C. Snell
Kevin Swersky
R. Zemel
285
8,129
0
15 Mar 2017
Deep Sets
Deep Sets
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
384
2,459
0
10 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
806
11,866
0
09 Mar 2017
Learning to learn by gradient descent by gradient descent
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz
Misha Denil
Sergio Gomez Colmenarejo
Matthew W. Hoffman
David Pfau
Tom Schaul
Brendan Shillingford
Nando de Freitas
99
2,004
0
14 Jun 2016
Matching Networks for One Shot Learning
Matching Networks for One Shot Learning
Oriol Vinyals
Charles Blundell
Timothy Lillicrap
Koray Kavukcuoglu
Daan Wierstra
VLM
351
7,316
0
13 Jun 2016
Towards a Neural Statistician
Towards a Neural Statistician
Harrison Edwards
Amos Storkey
BDL
70
427
0
07 Jun 2016
One-Shot Generalization in Deep Generative Models
One-Shot Generalization in Deep Generative Models
Danilo Jimenez Rezende
S. Mohamed
Ivo Danihelka
Karol Gregor
Daan Wierstra
BDL
VLM
DRL
LRM
103
254
0
16 Mar 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.6K
150,006
0
22 Dec 2014
Word Network Topic Model: A Simple but General Solution for Short and
  Imbalanced Texts
Word Network Topic Model: A Simple but General Solution for Short and Imbalanced Texts
Y. Zuo
Jichang Zhao
Ke Xu
47
179
0
17 Dec 2014
Transfer Topic Modeling with Ease and Scalability
Transfer Topic Modeling with Ease and Scalability
Jeon-Hyung Kang
Jun Ma
Yan Liu
53
27
0
24 Jan 2013
Probabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis
Thomas Hofmann
413
2,808
0
23 Jan 2013
Supervised Topic Models
Supervised Topic Models
David M. Blei
Jon D. McAuliffe
BDL
114
1,788
0
03 Mar 2010
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