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1906.02629
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When Does Label Smoothing Help?
Neural Information Processing Systems (NeurIPS), 2019
6 June 2019
Rafael Müller
Simon Kornblith
Geoffrey E. Hinton
UQCV
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Papers citing
"When Does Label Smoothing Help?"
37 / 987 papers shown
Meta Pseudo Labels
Computer Vision and Pattern Recognition (CVPR), 2020
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Zihang Dai
Qizhe Xie
Minh-Thang Luong
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732
0
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A comprehensive study on the prediction reliability of graph neural networks for virtual screening
Soojung Yang
K. Lee
Seongok Ryu
117
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0
17 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
International Conference on Machine Learning (ICML), 2020
Jize Zhang
B. Kailkhura
T. Y. Han
UQCV
325
257
0
16 Mar 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Neural Information Processing Systems (NeurIPS), 2020
Amir M. Rahimi
Amirreza Shaban
Ching-An Cheng
Leonid Sigal
Byron Boots
UQCV
461
80
0
15 Mar 2020
Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning
AAAI Conference on Artificial Intelligence (AAAI), 2020
Zhiqiang Shen
Zechun Liu
Zhuang Liu
Marios Savvides
Trevor Darrell
Eric P. Xing
OCL
SSL
393
114
0
11 Mar 2020
Does label smoothing mitigate label noise?
International Conference on Machine Learning (ICML), 2020
Michal Lukasik
Srinadh Bhojanapalli
A. Menon
Surinder Kumar
NoLa
341
392
0
05 Mar 2020
Double Backpropagation for Training Autoencoders against Adversarial Attack
Chengjin Sun
Sizhe Chen
Xiaolin Huang
SILM
AAML
191
5
0
04 Mar 2020
Towards Noise-resistant Object Detection with Noisy Annotations
Junnan Li
Caiming Xiong
R. Socher
Guosheng Lin
ObjD
NoLa
302
35
0
03 Mar 2020
Quantile Regularization: Towards Implicit Calibration of Regression Models
Saiteja Utpala
Piyush Rai
UQCV
105
10
0
28 Feb 2020
Calibrating Deep Neural Networks using Focal Loss
Neural Information Processing Systems (NeurIPS), 2020
Jishnu Mukhoti
Viveka Kulharia
Amartya Sanyal
Stuart Golodetz
Juil Sock
P. Dokania
UQCV
305
563
0
21 Feb 2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
International Conference on Machine Learning (ICML), 2020
Jian Liang
Dapeng Hu
Jiashi Feng
539
1,504
0
20 Feb 2020
Distance-Based Regularisation of Deep Networks for Fine-Tuning
International Conference on Learning Representations (ICLR), 2020
Henry Gouk
Timothy M. Hospedales
Massimiliano Pontil
246
61
0
19 Feb 2020
Being Bayesian about Categorical Probability
International Conference on Machine Learning (ICML), 2020
Taejong Joo
U. Chung
Minji Seo
UQCV
BDL
273
67
0
19 Feb 2020
Regularized Evolutionary Population-Based Training
Annual Conference on Genetic and Evolutionary Computation (GECCO), 2020
J. Liang
Santiago Gonzalez
Hormoz Shahrzad
Risto Miikkulainen
336
9
0
11 Feb 2020
Understanding and Improving Knowledge Distillation
Jiaxi Tang
Rakesh Shivanna
Zhe Zhao
Dong Lin
Anima Singh
Ed H. Chi
Sagar Jain
331
153
0
10 Feb 2020
Temporal Probability Calibration
Tim Leathart
Maksymilian C. Polaczuk
122
7
0
07 Feb 2020
Deep Learning for Person Re-identification: A Survey and Outlook
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Mang Ye
Jianbing Shen
Gaojie Lin
Tao Xiang
Ling Shao
Guosheng Lin
585
1,966
0
13 Jan 2020
Regularization via Structural Label Smoothing
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Weizhi Li
Gautam Dasarathy
Visar Berisha
UQCV
340
57
0
07 Jan 2020
Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
International Conference on Learning Representations (ICLR), 2020
Yixiao Ge
Dapeng Chen
Jiaming Song
301
632
0
06 Jan 2020
Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks
Computer Vision and Pattern Recognition (CVPR), 2019
Luca Bertinetto
Romain Mueller
Konstantinos Tertikas
Sina Samangooei
Nicholas A. Lord
OOD
416
162
0
19 Dec 2019
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Davood Karimi
Haoran Dou
Simon K. Warfield
Ali Gholipour
NoLa
376
618
0
05 Dec 2019
Distance-Based Learning from Errors for Confidence Calibration
International Conference on Learning Representations (ICLR), 2019
Chen Xing
Sercan O. Arik
Zizhao Zhang
Tomas Pfister
FedML
217
42
0
03 Dec 2019
E-Stitchup: Data Augmentation for Pre-Trained Embeddings
Cameron R. Wolfe
Keld T. Lundgaard
144
4
0
28 Nov 2019
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks
Katherine L. Hermann
Ting Chen
Simon Kornblith
CVBM
366
21
0
20 Nov 2019
Label-similarity Curriculum Learning
European Conference on Computer Vision (ECCV), 2019
Ürün Dogan
A. Deshmukh
Marcin Machura
Christian Igel
152
22
0
15 Nov 2019
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels
Hieu H. Pham
T. Le
Dat Q. Tran
Dat Ngo
H. Nguyen
293
33
0
15 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks
Shai Rozenberg
G. Elidan
Ran El-Yaniv
AAML
120
1
0
03 Nov 2019
Transformers without Tears: Improving the Normalization of Self-Attention
International Workshop on Spoken Language Translation (IWSLT), 2019
Toan Q. Nguyen
Julian Salazar
271
246
0
14 Oct 2019
Noise as a Resource for Learning in Knowledge Distillation
Elahe Arani
F. Sarfraz
Bahram Zonooz
180
6
0
11 Oct 2019
Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector
Jiaxing Huang
Seungwon Lee
Jingyi Zhang
Taegyun Jeon
151
6
0
04 Oct 2019
Revisiting Knowledge Distillation via Label Smoothing Regularization
Li-xin Yuan
Francis E. H. Tay
Guilin Li
Tao Wang
Jiashi Feng
163
97
0
25 Sep 2019
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
Asma Ghandeharioun
B. Eoff
Brendan Jou
Rosalind W. Picard
UD
UQCV
139
18
0
20 Sep 2019
Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
Automatic Speech Recognition & Understanding (ASRU), 2019
Yiming Wang
Tongfei Chen
Hainan Xu
Shuoyang Ding
Hang Lv
Yiwen Shao
Nanyun Peng
Lei Xie
Shinji Watanabe
Sanjeev Khudanpur
VLM
178
75
0
18 Sep 2019
Defending Against Adversarial Attacks by Suppressing the Largest Eigenvalue of Fisher Information Matrix
Yaxin Peng
Chaomin Shen
Guixu Zhang
Jinsong Fan
AAML
131
13
0
13 Sep 2019
On Regularization Properties of Artificial Datasets for Deep Learning
Computer Science and Mathematical Modelling (CSMM), 2019
K. Antczak
70
5
0
19 Aug 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
Neural Information Processing Systems (NeurIPS), 2019
S. Thulasidasan
Gopinath Chennupati
J. Bilmes
Tanmoy Bhattacharya
S. Michalak
UQCV
538
586
0
27 May 2019
Object Detection in 20 Years: A Survey
Proceedings of the IEEE (Proc. IEEE), 2019
Zhengxia Zou
Keyan Chen
Zhenwei Shi
Yuhong Guo
Jieping Ye
VLM
ObjD
AI4TS
473
3,041
0
13 May 2019
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