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Diversity Helps: Unsupervised Few-shot Learning via Distribution
  Shift-based Data Augmentation
v1v2 (latest)

Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation

13 April 2020
Tiexin Qin
Wenbin Li
Yinghuan Shi
Yang Gao
ArXiv (abs)PDFHTMLGithub (26★)

Papers citing "Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation"

10 / 10 papers shown
GeNIe: Generative Hard Negative Images Through Diffusion
GeNIe: Generative Hard Negative Images Through Diffusion
Soroush Abbasi Koohpayegani
Anuj Singh
K. Navaneet
Hadi Jamali Rad
Hamed Pirsiavash
VLMDiffM
382
7
0
05 Dec 2023
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised
  Meta-Learning
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-LearningEuropean Conference on Computer Vision (ECCV), 2022
Xingping Dong
Jianbing Shen
Ling Shao
232
18
0
27 Sep 2022
Self-Supervision Can Be a Good Few-Shot Learner
Self-Supervision Can Be a Good Few-Shot LearnerEuropean Conference on Computer Vision (ECCV), 2022
Yuning Lu
Liangjiang Wen
Jianzhuang Liu
Yajing Liu
Xinmei Tian
SSL
292
55
0
19 Jul 2022
Few-Shot Electronic Health Record Coding through Graph Contrastive
  Learning
Few-Shot Electronic Health Record Coding through Graph Contrastive Learning
Shanshan Wang
Sudipta Singha Roy
Zhumin Chen
Zhaochun Ren
Huasheng Liang
Qiang Yan
Evangelos Kanoulas
Maarten de Rijke
229
8
0
29 Jun 2021
Trainable Class Prototypes for Few-Shot Learning
Trainable Class Prototypes for Few-Shot Learning
Jianyi Li
Guizhong Liu
VLM
237
2
0
21 Jun 2021
A novel multiple instance learning framework for COVID-19 severity
  assessment via data augmentation and self-supervised learning
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learningMedical Image Analysis (MedIA), 2021
Ze-kun Li
Wei Zhao
F. Shi
Lei Qi
Xingzhi Xie
...
Yang Gao
Shangjie Wu
Jun Liu
Yinghuan Shi
Dinggang Shen
190
64
0
07 Feb 2021
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot
  Learning
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot LearningConference on Uncertainty in Artificial Intelligence (UAI), 2021
Yizhao Gao
Nanyi Fei
Guangzhen Liu
Zhiwu Lu
Tao Xiang
Songfang Huang
322
47
0
23 Jan 2021
Revisiting Unsupervised Meta-Learning via the Characteristics of
  Few-Shot Tasks
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot TasksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Han-Jia Ye
Lu Han
De-Chuan Zhan
OffRLSSLVLM
255
39
0
30 Nov 2020
Few-Shot Image Classification via Contrastive Self-Supervised Learning
Few-Shot Image Classification via Contrastive Self-Supervised Learning
Jianyi Li
Guizhong Liu
VLMSSLMQ
162
16
0
23 Aug 2020
Self-Supervised Prototypical Transfer Learning for Few-Shot
  Classification
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
Carlos Medina
A. Devos
Matthias Grossglauser
SSL
252
57
0
19 Jun 2020
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