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mixup: Beyond Empirical Risk Minimization
v1v2 (latest)

mixup: Beyond Empirical Risk Minimization

International Conference on Learning Representations (ICLR), 2017
25 October 2017
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
    NoLa
ArXiv (abs)PDFHTML

Papers citing "mixup: Beyond Empirical Risk Minimization"

50 / 5,331 papers shown
Robust and On-the-fly Dataset Denoising for Image Classification
Robust and On-the-fly Dataset Denoising for Image ClassificationEuropean Conference on Computer Vision (ECCV), 2020
Jiaming Song
Lunjia Hu
Michael Auli
Yann N. Dauphin
Tengyu Ma
NoLaOOD
179
13
0
24 Mar 2020
Meta Pseudo Labels
Meta Pseudo LabelsComputer Vision and Pattern Recognition (CVPR), 2020
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
1.1K
735
0
23 Mar 2020
Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus
  Images via Adversarial Domain Adaptation
Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation
Lie Ju
Xin Wang
Quan-Gen Zhou
Hu Zhu
Mehrtash Harandi
Paul Bonnington
Tom Drummond
Zongyuan Ge
MedIm
163
8
0
23 Mar 2020
Dynamic ReLU
Dynamic ReLUEuropean Conference on Computer Vision (ECCV), 2020
Yinpeng Chen
Xiyang Dai
Xiyang Dai
Dongdong Chen
Lu Yuan
Zicheng Liu
412
194
0
22 Mar 2020
On Calibration of Mixup Training for Deep Neural Networks
On Calibration of Mixup Training for Deep Neural NetworksInternational Workshop on Structural and Syntactic Pattern Recognition (SSPR), 2020
Juan Maroñas
D. Ramos-Castro
Roberto Paredes Palacios
UQCV
250
7
0
22 Mar 2020
BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of
  Channels
BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of Channels
Zan Shen
Jiang Qian
Bojin Zhuang
Shaojun Wang
Jing Xiao
161
5
0
22 Mar 2020
Review of data analysis in vision inspection of power lines with an
  in-depth discussion of deep learning technology
Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology
Xinyu Liu
Xiren Miao
Hao Jiang
Jia Chen
129
14
0
22 Mar 2020
ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging
ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging
T. Bdair
Benedikt Wiestler
Nassir Navab
Shadi Albarqouni
215
10
0
20 Mar 2020
Acoustic Scene Classification with Squeeze-Excitation Residual Networks
Acoustic Scene Classification with Squeeze-Excitation Residual Networks
Javier Naranjo-Alcazar
Sergi Perez-Castanos
P. Zuccarello
M. Cobos
137
0
0
20 Mar 2020
FocalMix: Semi-Supervised Learning for 3D Medical Image Detection
FocalMix: Semi-Supervised Learning for 3D Medical Image DetectionComputer Vision and Pattern Recognition (CVPR), 2020
Dong Wang
Yuan Zhang
Kexin Zhang
Liwei Wang
240
133
0
20 Mar 2020
Semi-Supervised Semantic Segmentation with Cross-Consistency Training
Semi-Supervised Semantic Segmentation with Cross-Consistency TrainingComputer Vision and Pattern Recognition (CVPR), 2020
Yassine Ouali
C´eline Hudelot
Myriam Tami
508
874
0
19 Mar 2020
Ensemble learning in CNN augmented with fully connected subnetworks
Ensemble learning in CNN augmented with fully connected subnetworks
Daiki Hirata
Norikazu Takahashi
OOD
140
30
0
19 Mar 2020
Semi-supervised Contrastive Learning Using Partial Label Information
Semi-supervised Contrastive Learning Using Partial Label Information
Colin B. Hansen
V. Nath
Diego A. Mesa
Yuankai Huo
Bennett A. Landman
Thomas A. Lasko
SSL
130
0
0
17 Mar 2020
A comprehensive study on the prediction reliability of graph neural
  networks for virtual screening
A comprehensive study on the prediction reliability of graph neural networks for virtual screening
Soojung Yang
K. Lee
Seongok Ryu
121
7
0
17 Mar 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural
  Networks
Intra Order-preserving Functions for Calibration of Multi-Class Neural NetworksNeural Information Processing Systems (NeurIPS), 2020
Amir M. Rahimi
Amirreza Shaban
Ching-An Cheng
Leonid Sigal
Byron Boots
UQCV
474
80
0
15 Mar 2020
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models
NoiseRank: Unsupervised Label Noise Reduction with Dependence ModelsEuropean Conference on Computer Vision (ECCV), 2020
Karishma Sharma
Pinar E. Donmez
Enming Luo
Yan Liu
I. Z. Yalniz
NoLa
205
37
0
15 Mar 2020
On the benefits of defining vicinal distributions in latent space
On the benefits of defining vicinal distributions in latent spacePattern Recognition Letters (Pattern Recognit. Lett.), 2020
Puneet Mangla
Vedant Singh
Shreyas Jayant Havaldar
V. Balasubramanian
AAML
211
4
0
14 Mar 2020
Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation
  Learning
Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation LearningAAAI Conference on Artificial Intelligence (AAAI), 2020
Zhiqiang Shen
Zechun Liu
Zhuang Liu
Marios Savvides
Trevor Darrell
Eric P. Xing
OCLSSL
393
114
0
11 Mar 2020
SuperMix: Supervising the Mixing Data Augmentation
SuperMix: Supervising the Mixing Data AugmentationComputer Vision and Pattern Recognition (CVPR), 2020
Ali Dabouei
Sobhan Soleymani
Fariborz Taherkhani
Nasser M. Nasrabadi
348
117
0
10 Mar 2020
Embedding Propagation: Smoother Manifold for Few-Shot Classification
Embedding Propagation: Smoother Manifold for Few-Shot ClassificationEuropean Conference on Computer Vision (ECCV), 2020
Pau Rodríguez
I. Laradji
Alexandre Drouin
Alexandre Lacoste
243
207
0
09 Mar 2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization
  Methods
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods
Sanghyuk Chun
Seong Joon Oh
Sangdoo Yun
Dongyoon Han
Junsuk Choe
Y. Yoo
AAMLOOD
680
54
0
09 Mar 2020
DADA: Differentiable Automatic Data Augmentation
DADA: Differentiable Automatic Data AugmentationEuropean Conference on Computer Vision (ECCV), 2020
Yonggang Li
Guosheng Hu
Yongtao Wang
Timothy M. Hospedales
N. Robertson
Yongxin Yang
337
116
0
08 Mar 2020
Semi-Supervised StyleGAN for Disentanglement Learning
Semi-Supervised StyleGAN for Disentanglement LearningInternational Conference on Machine Learning (ICML), 2020
Weili Nie
Tero Karras
Animesh Garg
Shoubhik Debhath
Anjul Patney
Ankit B. Patel
Anima Anandkumar
DRL
254
77
0
06 Mar 2020
Does label smoothing mitigate label noise?
Does label smoothing mitigate label noise?International Conference on Machine Learning (ICML), 2020
Michal Lukasik
Srinadh Bhojanapalli
A. Menon
Surinder Kumar
NoLa
341
393
0
05 Mar 2020
Embedding Expansion: Augmentation in Embedding Space for Deep Metric
  Learning
Embedding Expansion: Augmentation in Embedding Space for Deep Metric LearningComputer Vision and Pattern Recognition (CVPR), 2020
ByungSoo Ko
Geonmo Gu
265
60
0
05 Mar 2020
A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
A Balanced and Uncertainty-aware Approach for Partial Domain AdaptationEuropean Conference on Computer Vision (ECCV), 2020
Jian Liang
Yunbo Wang
Dapeng Hu
Ran He
Jiashi Feng
362
118
0
05 Mar 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust
  Generalization
Adversarial Vertex Mixup: Toward Better Adversarially Robust GeneralizationComputer Vision and Pattern Recognition (CVPR), 2020
Saehyung Lee
Hyungyu Lee
Sungroh Yoon
AAML
523
134
0
05 Mar 2020
Mixup Regularization for Region Proposal based Object Detectors
Mixup Regularization for Region Proposal based Object Detectors
S. Bouabid
V. Delaitre
ObjD
129
5
0
04 Mar 2020
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised
  Knee Osteoarthritis Severity Grading from Plain Radiographs
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain RadiographsIEEE Transactions on Medical Imaging (TMI), 2020
Huy Hoang Nguyen
S. Saarakkala
Matthew Blaschko
A. Tiulpin
222
50
0
04 Mar 2020
A New Dataset, Poisson GAN and AquaNet for Underwater Object Grabbing
A New Dataset, Poisson GAN and AquaNet for Underwater Object Grabbing
Chongwei Liu
Zhihui Wang
Shijie Wang
Tao Tang
Yulong Tao
Caifei Yang
Haojie Li
Xing Liu
Xin-Yue Fan
170
80
0
03 Mar 2020
Iterative Averaging in the Quest for Best Test Error
Iterative Averaging in the Quest for Best Test ErrorJournal of machine learning research (JMLR), 2020
Diego Granziol
Xingchen Wan
Samuel Albanie
Stephen J. Roberts
290
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0
02 Mar 2020
Learning Cross-domain Generalizable Features by Representation
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Qingjie Meng
Daniel Rueckert
Bernhard Kainz
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167
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29 Feb 2020
Introduction to deep learning
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Lihi Shiloh-Perl
Raja Giryes
162
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29 Feb 2020
Do CNNs Encode Data Augmentations?
Do CNNs Encode Data Augmentations?IEEE International Joint Conference on Neural Network (IJCNN), 2020
Eddie Q. Yan
Yanping Huang
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157
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Quantile Regularization: Towards Implicit Calibration of Regression
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Saiteja Utpala
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A U-Net Based Discriminator for Generative Adversarial Networks
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Membership Inference Attacks and Defenses in Classification Models
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FMix: Enhancing Mixed Sample Data Augmentation
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Ethan Harris
Antonia Marcu
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Towards Utilizing Unlabeled Data in Federated Learning: A Survey and
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On Feature Normalization and Data Augmentation
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Ser-Nam Lim
Serge J. Belongie
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PointAugment: an Auto-Augmentation Framework for Point Cloud
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Self-Adaptive Training: beyond Empirical Risk Minimization
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Chaoning Zhang
Hongyang R. Zhang
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Multi-Representation Knowledge Distillation For Audio Classification
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Greedy Policy Search: A Simple Baseline for Learnable Test-Time
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MaxUp: A Simple Way to Improve Generalization of Neural Network Training
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Wavesplit: End-to-End Speech Separation by Speaker Clustering
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A survey on Semi-, Self- and Unsupervised Learning for Image
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