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Discriminative k-shot learning using probabilistic models
v1v2 (latest)

Discriminative k-shot learning using probabilistic models

1 June 2017
Matthias Bauer
Mateo Rojas-Carulla
J. Swiatkowski
Bernhard Schölkopf
Richard Turner
    VLM
ArXiv (abs)PDFHTML

Papers citing "Discriminative k-shot learning using probabilistic models"

38 / 38 papers shown
Title
How to Do Machine Learning with Small Data? -- A Review from an
  Industrial Perspective
How to Do Machine Learning with Small Data? -- A Review from an Industrial Perspective
I. Kraljevski
Yong Chul Ju
Dmitrij Ivanov
Constanze Tschope
M. Wolff
AI4CE
64
4
0
13 Nov 2023
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot
  Policy Imitation
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation
Massimiliano Patacchiola
Mingfei Sun
Katja Hofmann
Richard Turner
OffRL
71
1
0
23 Jun 2023
Hypernetwork approach to Bayesian MAML
Hypernetwork approach to Bayesian MAML
Piotr Borycki
Piotr Kubacki
Marcin Przewiȩźlikowski
Tomasz Kuśmierczyk
Jacek Tabor
Przemysław Spurek
BDL
53
2
0
06 Oct 2022
Blind Users Accessing Their Training Images in Teachable Object
  Recognizers
Blind Users Accessing Their Training Images in Teachable Object Recognizers
Jonggi Hong
Jaina Gandhi
Ernest Essuah Mensah
Farnaz Zamiri Zeraati
Ebrima Jarjue
Kyungjun Lee
Hernisa Kacorri
VLM
81
16
0
16 Aug 2022
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image
  Classification
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Massimiliano Patacchiola
J. Bronskill
Aliaksandra Shysheya
Katja Hofmann
Sebastian Nowozin
Richard Turner
VLM
72
10
0
20 Jun 2022
HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks
HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks
Marcin Przewiȩźlikowski
P. Przybysz
Jacek Tabor
Maciej Ziȩba
Przemysław Spurek
108
20
0
31 May 2022
HyperShot: Few-Shot Learning by Kernel HyperNetworks
HyperShot: Few-Shot Learning by Kernel HyperNetworks
Marcin Sendera
Marcin Przewiȩźlikowski
Konrad Karanowski
Maciej Ziȩba
Jacek Tabor
Przemysław Spurek
VLM
98
29
0
21 Mar 2022
The Internet of Federated Things (IoFT): A Vision for the Future and
  In-depth Survey of Data-driven Approaches for Federated Learning
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
Raed Al Kontar
Naichen Shi
Xubo Yue
Seokhyun Chung
E. Byon
...
Chinedum Okwudire
Garvesh Raskutti
R. Saigal
Karandeep Singh
Ye Zhisheng
FedML
106
52
0
09 Nov 2021
Simultaneous Perturbation Method for Multi-Task Weight Optimization in
  One-Shot Meta-Learning
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning
Andrei Boiarov
K. Khabarlak
Igor Yastrebov
148
0
0
25 Oct 2021
Learning by Examples Based on Multi-level Optimization
Learning by Examples Based on Multi-level Optimization
Shentong Mo
P. Xie
64
0
0
22 Sep 2021
A Transductive Maximum Margin Classifier for Few-Shot Learning
A Transductive Maximum Margin Classifier for Few-Shot Learning
Fei Pan
Chunlei Xu
Jie Guo
Yanwen Guo
43
0
0
26 Jul 2021
MetaKernel: Learning Variational Random Features with Limited Labels
MetaKernel: Learning Variational Random Features with Limited Labels
Yingjun Du
Haoliang Sun
Xiantong Zhen
Jun Xu
Yilong Yin
Ling Shao
Cees G. M. Snoek
VLMBDL
37
5
0
08 May 2021
Multimodal Prototypical Networks for Few-shot Learning
Multimodal Prototypical Networks for Few-shot Learning
Frederik Pahde
M. Puscas
T. Klein
Moin Nabi
77
90
0
17 Nov 2020
A Survey on Machine Learning from Few Samples
A Survey on Machine Learning from Few Samples
Jiang Lu
Pinghua Gong
Jieping Ye
Jianwei Zhang
Changshu Zhang
98
52
0
06 Sep 2020
Learning from Few Samples: A Survey
Learning from Few Samples: A Survey
Nihar Bendre
Hugo Terashima-Marín
Peyman Najafirad
VLMBDL
87
54
0
30 Jul 2020
Learning to Learn Kernels with Variational Random Features
Learning to Learn Kernels with Variational Random Features
Xiantong Zhen
Hao Sun
Yingjun Du
Jun Xu
Yilong Yin
Ling Shao
Cees G. M. Snoek
DRL
72
34
0
11 Jun 2020
Embedding Propagation: Smoother Manifold for Few-Shot Classification
Embedding Propagation: Smoother Manifold for Few-Shot Classification
Pau Rodríguez
I. Laradji
Alexandre Drouin
Alexandre Lacoste
73
196
0
09 Mar 2020
Semantic Regularization: Improve Few-shot Image Classification by
  Reducing Meta Shift
Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift
Da Chen
Yongliang Yang
Zunlei Feng
Xiang Wu
Min-Gyoo Song
Wenbin Li
Yuan He
Hui Xue
Feng Mao
VLM
23
1
0
18 Dec 2019
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
75
68
0
05 Dec 2019
Self-Supervised Learning For Few-Shot Image Classification
Self-Supervised Learning For Few-Shot Image Classification
Da Chen
YueFeng Chen
Yuhong Li
Feng Mao
Yuan He
Hui Xue
SSL
73
110
0
14 Nov 2019
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot
  Learning
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning
Yan Wang
Wei-Lun Chao
Kilian Q. Weinberger
Laurens van der Maaten
VLM
89
343
0
12 Nov 2019
Neural Similarity Learning
Neural Similarity Learning
Weiyang Liu
Zhen Liu
James M. Rehg
Le Song
94
30
0
28 Oct 2019
Meta-Transfer Learning through Hard Tasks
Meta-Transfer Learning through Hard Tasks
Qianru Sun
Yaoyao Liu
Zhaozheng Chen
Tat-Seng Chua
Bernt Schiele
102
102
0
07 Oct 2019
Decoder Choice Network for Meta-Learning
Decoder Choice Network for Meta-Learning
Jialin Liu
Chia-Wen Lin
Longzhi Yang
Chih-Min Lin
Q. Shen
31
9
0
25 Sep 2019
Adaptive Wasserstein Hourglass for Weakly Supervised Hand Pose
  Estimation from Monocular RGB
Adaptive Wasserstein Hourglass for Weakly Supervised Hand Pose Estimation from Monocular RGB
Yumeng Zhang
Li Chen
Yufeng Liu
Junhai Yong
Wen Zheng
3DH
26
7
0
11 Sep 2019
Relational Generalized Few-Shot Learning
Relational Generalized Few-Shot Learning
Xiahan Shi
Leonard Salewski
Martin Schiegg
Zeynep Akata
Max Welling
78
24
0
22 Jul 2019
Fast and Flexible Multi-Task Classification Using Conditional Neural
  Adaptive Processes
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
James Requeima
Jonathan Gordon
J. Bronskill
Sebastian Nowozin
Richard Turner
76
243
0
18 Jun 2019
Hyperbolic Image Embeddings
Hyperbolic Image Embeddings
Valentin Khrulkov
L. Mirvakhabova
E. Ustinova
Ivan Oseledets
Victor Lempitsky
106
296
0
03 Apr 2019
Meta-Learning surrogate models for sequential decision making
Meta-Learning surrogate models for sequential decision making
Alexandre Galashov
Jonathan Richard Schwarz
Hyunjik Kim
M. Garnelo
D. Saxton
Pushmeet Kohli
S. M. Ali Eslami
Yee Whye Teh
BDLOffRL
95
25
0
28 Mar 2019
Adaptive Cross-Modal Few-Shot Learning
Adaptive Cross-Modal Few-Shot Learning
Chen Xing
Negar Rostamzadeh
Boris N. Oreshkin
Pedro H. O. Pinheiro
148
275
0
19 Feb 2019
Reconciling meta-learning and continual learning with online mixtures of
  tasks
Reconciling meta-learning and continual learning with online mixtures of tasks
Ghassen Jerfel
Erin Grant
Thomas Griffiths
Katherine A. Heller
FedMLCLLBDL
100
12
0
14 Dec 2018
Meta-Learning Priors for Efficient Online Bayesian Regression
Meta-Learning Priors for Efficient Online Bayesian Regression
James Harrison
Apoorva Sharma
Marco Pavone
BDL
84
102
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
154
1,374
0
16 Jul 2018
Uncertainty in Multitask Transfer Learning
Uncertainty in Multitask Transfer Learning
Alexandre Lacoste
Boris N. Oreshkin
Wonchang Chung
Thomas Boquet
Negar Rostamzadeh
David M. Krueger
BDLUQCVSSL
105
21
0
20 Jun 2018
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCVBDL
309
504
0
11 Jun 2018
Learning to Propagate Labels: Transductive Propagation Network for
  Few-shot Learning
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu
Juho Lee
Minseop Park
Saehoon Kim
Eunho Yang
Sung Ju Hwang
Yi Yang
116
670
0
25 May 2018
Meta-Learning Probabilistic Inference For Prediction
Meta-Learning Probabilistic Inference For Prediction
Jonathan Gordon
J. Bronskill
Matthias Bauer
Sebastian Nowozin
Richard Turner
BDL
134
265
0
24 May 2018
TADAM: Task dependent adaptive metric for improved few-shot learning
TADAM: Task dependent adaptive metric for improved few-shot learning
Boris N. Oreshkin
Pau Rodríguez López
Alexandre Lacoste
115
1,317
0
23 May 2018
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