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Predicting the Accuracy of a Few-Shot Classifier

Predicting the Accuracy of a Few-Shot Classifier

8 July 2020
Myriam Bontonou
Louis Bethune
Vincent Gripon
ArXiv (abs)PDFHTML

Papers citing "Predicting the Accuracy of a Few-Shot Classifier"

27 / 27 papers shown
Title
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
Timo Milbich
Karsten Roth
Homanga Bharadhwaj
Samarth Sinha
Yoshua Bengio
Bjorn Ommer
Joseph Paul Cohen
92
66
0
28 Apr 2020
TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot
  classification
TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification
M. Lichtenstein
P. Sattigeri
Rogerio Feris
Raja Giryes
Leonid Karlinsky
83
77
0
14 Mar 2020
A Theory of Usable Information Under Computational Constraints
A Theory of Usable Information Under Computational Constraints
Yilun Xu
Shengjia Zhao
Jiaming Song
Russell Stewart
Stefano Ermon
75
174
0
25 Feb 2020
Graph-based Interpolation of Feature Vectors for Accurate Few-Shot
  Classification
Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification
Yuqing Hu
Vincent Gripon
S. Pateux
55
28
0
27 Jan 2020
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
69
340
0
12 Nov 2019
Learning Disentangled Representations for Recommendation
Learning Disentangled Representations for Recommendation
Jianxin Ma
Chang Zhou
Peng Cui
Hongxia Yang
Wenwu Zhu
CMLDRL
90
309
0
31 Oct 2019
Charting the Right Manifold: Manifold Mixup for Few-shot Learning
Charting the Right Manifold: Manifold Mixup for Few-shot Learning
Puneet Mangla
M. Singh
Abhishek Sinha
Nupur Kumari
V. Balasubramanian
Balaji Krishnamurthy
SSL
89
328
0
28 Jul 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
192
2,229
0
05 Jul 2019
A Closer Look at Few-shot Classification
A Closer Look at Few-shot Classification
Wei-Yu Chen
Yen-Cheng Liu
Z. Kira
Y. Wang
Jia-Bin Huang
114
1,767
0
08 Apr 2019
Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions
Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions
Han-Jia Ye
Hexiang Hu
De-Chuan Zhan
Fei Sha
127
666
0
10 Dec 2018
Learning deep representations by mutual information estimation and
  maximization
Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm
A. Fedorov
Samuel Lavoie-Marchildon
Karan Grewal
Phil Bachman
Adam Trischler
Yoshua Bengio
SSLDRL
320
2,662
0
20 Aug 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
139
1,371
0
16 Jul 2018
Object Detection with Deep Learning: A Review
Object Detection with Deep Learning: A Review
Zhong-Qiu Zhao
Peng Zheng
Shou-tao Xu
Xindong Wu
ObjD
110
4,012
0
15 Jul 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
96
1,313
0
23 May 2018
Meta-Learning for Semi-Supervised Few-Shot Classification
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren
Eleni Triantafillou
S. S. Ravi
Jake C. Snell
Kevin Swersky
J. Tenenbaum
Hugo Larochelle
R. Zemel
SSL
70
1,283
0
02 Mar 2018
Learning to Compare: Relation Network for Few-Shot Learning
Learning to Compare: Relation Network for Few-Shot Learning
Flood Sung
Yongxin Yang
Li Zhang
Tao Xiang
Philip Torr
Timothy M. Hospedales
298
4,050
0
16 Nov 2017
Prototypical Networks for Few-shot Learning
Prototypical Networks for Few-shot Learning
Jake C. Snell
Kevin Swersky
R. Zemel
300
8,134
0
15 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
823
11,909
0
09 Mar 2017
SoundNet: Learning Sound Representations from Unlabeled Video
SoundNet: Learning Sound Representations from Unlabeled Video
Y. Aytar
Carl Vondrick
Antonio Torralba
SSL
115
1,044
0
27 Oct 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
772
36,813
0
25 Aug 2016
Matching Networks for One Shot Learning
Matching Networks for One Shot Learning
Oriol Vinyals
Charles Blundell
Timothy Lillicrap
Koray Kavukcuoglu
Daan Wierstra
VLM
373
7,323
0
13 Jun 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
340
7,985
0
23 May 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLMObjD
1.7K
39,547
0
01 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
560
27,311
0
01 Sep 2014
The Emerging Field of Signal Processing on Graphs: Extending
  High-Dimensional Data Analysis to Networks and Other Irregular Domains
The Emerging Field of Signal Processing on Graphs: Extending High-Dimensional Data Analysis to Networks and Other Irregular Domains
D. Shuman
S. K. Narang
P. Frossard
Antonio Ortega
P. Vandergheynst
130
3,974
0
31 Oct 2012
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OODSSL
264
12,439
0
24 Jun 2012
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