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1808.04572
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Small Sample Learning in Big Data Era
14 August 2018
Jun Shu
Zongben Xu
Deyu Meng
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Papers citing
"Small Sample Learning in Big Data Era"
36 / 36 papers shown
Improving Memory Efficiency for Training KANs via Meta Learning
Zhangchi Zhao
Jun Shu
Deyu Meng
Zongben Xu
193
2
0
09 Jun 2025
Hierarchical Local-Global Feature Learning for Few-shot Malicious Traffic Detection
Songtao Peng
Lei Wang
Wu Shuai
Hao Song
Jiajun Zhou
Jinsong Chen
Qi Xuan
378
0
0
01 Apr 2025
Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting
Tiange Zhang
Qing Cai
Feng Gao
Lin Qi
Junyu Dong
341
17
0
24 Jun 2024
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning
Jun Shu
Xiang Yuan
Deyu Meng
Zongben Xu
376
5
0
13 May 2023
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey
ACM Computing Surveys (ACM Comput. Surv.), 2023
Huali Xu
Shuaifeng Zhi
Shuzhou Sun
Vishal M. Patel
Tianpeng Liu
718
35
0
15 Mar 2023
Improve Noise Tolerance of Robust Loss via Noise-Awareness
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Kehui Ding
Jun Shu
Deyu Meng
Zongben Xu
NoLa
302
11
0
18 Jan 2023
The Lean Data Scientist: Recent Advances towards Overcoming the Data Bottleneck
Communications of the ACM (CACM), 2022
Chen Shani
Jonathan Zarecki
Dafna Shahaf
198
7
0
15 Nov 2022
Deep transfer learning for image classification: a survey
J. Plested
Musa Phiri
Tom Gedeon
OOD
306
50
0
20 May 2022
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities
ACM Computing Surveys (ACM CSUR), 2022
Yisheng Song
Ting-Yuan Wang
S. Mondal
J. P. Sahoo
SLR
473
641
0
13 May 2022
CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Jun Shu
Xiang Yuan
Deyu Meng
Zongben Xu
NoLa
330
64
0
11 Feb 2022
Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data
AAAI Conference on Artificial Intelligence (AAAI), 2021
Shenwang Jiang
Jianan Li
Ying Wang
Bo Huang
Zhang Zhang
Tingfa Xu
NoLa
180
46
0
30 Dec 2021
Coarse-To-Fine Incremental Few-Shot Learning
Xiang Xiang
Yuwen Tan
Qian Wan
Jing Ma
CLL
299
17
0
24 Nov 2021
Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks
Jun Shu
Deyu Meng
Zongben Xu
375
13
0
06 Jul 2021
What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2021
Yang Hu
Adriane P. Chapman
Guihua Wen
Dame Wendy Hall
329
27
0
11 Jun 2021
Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments
Pattern Recognition (Pattern Recogn.), 2021
Xiaoxu Li
Xiaochen Yang
Zhanyu Ma
Jing-Hao Xue
VLM
349
181
0
17 May 2021
Evaluating Predictive Business Process Monitoring Approaches on Small Event Logs
Quality of Information and Communications Technology (QICT), 2021
Martin Käppel
Stefan Jablonski
Stefan Schönig
149
12
0
01 Apr 2021
Machine learning on small size samples: A synthetic knowledge synthesis
Science in progress (SP), 2021
P. Kokol
Marko Kokol
S. Zagoranski
224
219
0
01 Mar 2021
A Survey on Machine Learning from Few Samples
Pattern Recognition (Pattern Recognit.), 2020
Jiang Lu
Pinghua Gong
Jieping Ye
Jianwei Zhang
Changshu Zhang
376
81
0
06 Sep 2020
Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction
Ziyi Yang
Jun Shu
Yong Liang
Deyu Meng
Zongben Xu
234
2
0
02 Sep 2020
MLR-SNet: Transferable LR Schedules for Heterogeneous Tasks
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Jun Shu
Yanwen Zhu
Qian Zhao
Zongben Xu
Deyu Meng
382
8
0
29 Jul 2020
Sample-based Regularization: A Transfer Learning Strategy Toward Better Generalization
Yunho Jeon
Yongseok Choi
Jaesun Park
Subin Yi
D.-Y. Cho
Jiwon Kim
166
6
0
10 Jul 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
Jun Shu
Qian Zhao
Zengben Xu
Deyu Meng
NoLa
283
32
0
10 Jun 2020
A Concise Review of Recent Few-shot Meta-learning Methods
Xiaoxu Li
Z. Sun
Jing-Hao Xue
Zhanyu Ma
VLM
OffRL
270
142
0
22 May 2020
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer
IEEE Transactions on Image Processing (TIP), 2020
Xiaoxu Li
Dongliang Chang
Zhanyu Ma
Zheng-Hua Tan
Jing-Hao Xue
Jie Cao
Jingyi Yu
Jun Guo
252
42
0
20 Apr 2020
Learning Adaptive Loss for Robust Learning with Noisy Labels
Jun Shu
Qian Zhao
Keyu Chen
Zongben Xu
Deyu Meng
NoLa
OOD
227
23
0
16 Feb 2020
A Two-Stage Approach to Few-Shot Learning for Image Recognition
IEEE Transactions on Image Processing (TIP), 2019
Debasmit Das
C. S. George Lee
274
140
0
10 Dec 2019
Multi-label Classification for Automatic Tag Prediction in the Context of Programming Challenges
Bianca Iancu
Gabriele Mazzola
Kyriakos Psarakis
Panagiotis Soilis
247
5
0
27 Nov 2019
Personalization of Deep Learning
Data Science (DS), 2019
Johannes Schneider
M. Vlachos
403
43
0
06 Sep 2019
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019
Quanyu Dai
Xiao-Ming Wu
Jiaren Xiao
Xiao Shen
Dan Wang
OOD
357
133
0
04 Sep 2019
Reinforcement Learning in Healthcare: A Survey
ACM Computing Surveys (ACM CSUR), 2019
Chao Yu
Jiming Liu
S. Nemati
LM&MA
OffRL
792
728
0
22 Aug 2019
A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
Pengyi Zhang
Yunxin Zhong
Yulin Deng
Xiaoying Tang
Xiaoqiong Li
309
34
0
01 Aug 2019
Interpretable Few-Shot Learning via Linear Distillation
Arip Asadulaev
Igor Kuznetsov
Andrey Filchenkov
FedML
FAtt
325
1
0
13 Jun 2019
Generalizing from a Few Examples: A Survey on Few-Shot Learning
Yaqing Wang
Quanming Yao
James T. Kwok
L. Ni
759
2,068
0
10 Apr 2019
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting
Jun Shu
Qi Xie
Lixuan Yi
Qian Zhao
Sanping Zhou
Zongben Xu
Deyu Meng
NoLa
462
5
0
20 Feb 2019
Adversarial Discriminative Domain Adaptation
Computer Vision and Pattern Recognition (CVPR), 2017
Eric Tzeng
Judy Hoffman
Kate Saenko
Trevor Darrell
GAN
OOD
1.5K
5,156
0
17 Feb 2017
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker
Matej Moravcík
Martin Schmid
Neil Burch
Viliam Lisý
Dustin Morrill
Nolan Bard
Trevor Davis
Kevin Waugh
Michael Bradley Johanson
Michael Bowling
BDL
672
988
0
06 Jan 2017
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