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Wide Residual Networks

Wide Residual Networks

23 May 2016
Sergey Zagoruyko
N. Komodakis
ArXivPDFHTML

Papers citing "Wide Residual Networks"

50 / 4,117 papers shown
Title
Federated Adversarial Learning for Robust Autonomous Landing Runway
  Detection
Federated Adversarial Learning for Robust Autonomous Landing Runway Detection
Yi Li
Plamen Angelov
Zhengxin Yu
Alvaro Lopez Pellicer
Neeraj Suri
39
2
0
22 Jun 2024
AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning
AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning
Zhiyu Wu
Jinshi Cui
51
2
0
22 Jun 2024
DataFreeShield: Defending Adversarial Attacks without Training Data
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee
Kanghyun Choi
Dain Kwon
Sunjong Park
Mayoore S. Jaiswal
Noseong Park
Jonghyun Choi
Jinho Lee
41
0
0
21 Jun 2024
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
Peter Lorenz
Mario Fernandez
Jens Müller
Ullrich Kothe
AAML
78
1
0
21 Jun 2024
Adaptive Adversarial Cross-Entropy Loss for Sharpness-Aware Minimization
Adaptive Adversarial Cross-Entropy Loss for Sharpness-Aware Minimization
Tanapat Ratchatorn
Masayuki Tanaka
AAML
44
0
0
20 Jun 2024
MEAT: Median-Ensemble Adversarial Training for Improving Robustness and
  Generalization
MEAT: Median-Ensemble Adversarial Training for Improving Robustness and Generalization
Zhaozhe Hu
Jia-Li Yin
Bin Chen
Luojun Lin
Bo-Hao Chen
Ximeng Liu
AAML
38
0
0
20 Jun 2024
Exploring Layerwise Adversarial Robustness Through the Lens of t-SNE
Exploring Layerwise Adversarial Robustness Through the Lens of t-SNE
Inês Valentim
Nuno Antunes
Nuno Lourenço
AAML
41
1
0
20 Jun 2024
You can't handle the (dirty) truth: Data-centric insights improve
  pseudo-labeling
You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling
Nabeel Seedat
Nicolas Huynh
F. Imrie
Mihaela van der Schaar
51
1
0
19 Jun 2024
Large-Scale Dataset Pruning in Adversarial Training through Data
  Importance Extrapolation
Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation
Bjorn Nieth
Thomas Altstidl
Leo Schwinn
Björn Eskofier
AAML
45
2
0
19 Jun 2024
Boosting Consistency in Dual Training for Long-Tailed Semi-Supervised
  Learning
Boosting Consistency in Dual Training for Long-Tailed Semi-Supervised Learning
Kai Gan
Tong Wei
Min-Ling Zhang
50
1
0
19 Jun 2024
DLP: towards active defense against backdoor attacks with decoupled
  learning process
DLP: towards active defense against backdoor attacks with decoupled learning process
Zonghao Ying
Bin Wu
AAML
51
6
0
18 Jun 2024
Online Anchor-based Training for Image Classification Tasks
Online Anchor-based Training for Image Classification Tasks
Maria Tzelepi
Vasileios Mezaris
16
0
0
18 Jun 2024
Federated Learning with a Single Shared Image
Federated Learning with a Single Shared Image
Sunny Soni
Aaqib Saeed
Yuki M. Asano
FedML
DD
56
1
0
18 Jun 2024
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing
  Adversarial Robustness
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness
Kejia Zhang
Juanjuan Weng
Junwei Wu
Guoqing Yang
Shaozi Li
Zhiming Luo
AAML
56
1
0
17 Jun 2024
NBA: defensive distillation for backdoor removal via neural behavior
  alignment
NBA: defensive distillation for backdoor removal via neural behavior alignment
Zonghao Ying
Bin Wu
AAML
31
6
0
16 Jun 2024
A Rate-Distortion View of Uncertainty Quantification
A Rate-Distortion View of Uncertainty Quantification
Ifigeneia Apostolopoulou
Benjamin Eysenbach
Frank Nielsen
Artur Dubrawski
UQCV
50
2
0
16 Jun 2024
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn
  Good Representations?
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
Mark Ibrahim
David Klindt
Randall Balestriero
SSL
56
2
1
15 Jun 2024
Tilt and Average : Geometric Adjustment of the Last Layer for
  Recalibration
Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
Gyusang Cho
Chan-Hyun Youn
35
0
0
14 Jun 2024
Why Warmup the Learning Rate? Underlying Mechanisms and Improvements
Why Warmup the Learning Rate? Underlying Mechanisms and Improvements
Dayal Singh Kalra
M. Barkeshli
62
7
0
13 Jun 2024
Potion: Towards Poison Unlearning
Potion: Towards Poison Unlearning
Stefan Schoepf
Jack Foster
Alexandra Brintrup
AAML
MU
57
7
0
13 Jun 2024
Improving Adversarial Robustness via Feature Pattern Consistency
  Constraint
Improving Adversarial Robustness via Feature Pattern Consistency Constraint
Jiacong Hu
Jingwen Ye
Zunlei Feng
Jiazhen Yang
Shunyu Liu
Xiaotian Yu
Lingxiang Jia
Mingli Song
AAML
54
2
0
13 Jun 2024
Decoupling the Class Label and the Target Concept in Machine Unlearning
Decoupling the Class Label and the Target Concept in Machine Unlearning
Jianing Zhu
Bo Han
Jiangchao Yao
Jianliang Xu
Gang Niu
Masashi Sugiyama
CLL
MU
34
4
0
12 Jun 2024
Adaptive Teaching with Shared Classifier for Knowledge Distillation
Adaptive Teaching with Shared Classifier for Knowledge Distillation
Jaeyeon Jang
Young-Ik Kim
Jisu Lim
Hyeonseong Lee
31
0
0
12 Jun 2024
Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization
Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization
Jiaxin Deng
Junbiao Pang
Baochang Zhang
71
1
0
12 Jun 2024
Towards Fundamentally Scalable Model Selection: Asymptotically Fast
  Update and Selection
Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection
Wenxiao Wang
Weiming Zhuang
Lingjuan Lyu
49
0
0
11 Jun 2024
PAC-Bayes Analysis for Recalibration in Classification
PAC-Bayes Analysis for Recalibration in Classification
Masahiro Fujisawa
Futoshi Futami
46
0
0
10 Jun 2024
Neural-g: A Deep Learning Framework for Mixing Density Estimation
Neural-g: A Deep Learning Framework for Mixing Density Estimation
Shijie Wang
Saptarshi Chakraborty
Qian Qin
Ray Bai
BDL
45
0
0
10 Jun 2024
Causality-inspired Latent Feature Augmentation for Single Domain
  Generalization
Causality-inspired Latent Feature Augmentation for Single Domain Generalization
Jian Xu
Chaojie Ji
Yankai Cao
Ye Li
Ruxin Wang
OOD
34
0
0
10 Jun 2024
ProFeAT: Projected Feature Adversarial Training for Self-Supervised
  Learning of Robust Representations
ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations
Sravanti Addepalli
Priyam Dey
R. Venkatesh Babu
52
0
0
09 Jun 2024
A Recover-then-Discriminate Framework for Robust Anomaly Detection
A Recover-then-Discriminate Framework for Robust Anomaly Detection
Peng-Fei Xing
Dong Zhang
Jinhui Tang
Zechao li
47
1
0
07 Jun 2024
Batch-in-Batch: a new adversarial training framework for initial
  perturbation and sample selection
Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection
Yinting Wu
Pai Peng
Bo Cai
Le Li
.
AAML
44
0
0
06 Jun 2024
ZeroPur: Succinct Training-Free Adversarial Purification
ZeroPur: Succinct Training-Free Adversarial Purification
Xiuli Bi
Zonglin Yang
Bo Liu
Xiaodong Cun
Chi-Man Pun
Pietro Liò
Bin Xiao
46
0
0
05 Jun 2024
VQUNet: Vector Quantization U-Net for Defending Adversarial Atacks by
  Regularizing Unwanted Noise
VQUNet: Vector Quantization U-Net for Defending Adversarial Atacks by Regularizing Unwanted Noise
Zhixun He
Mukesh Singhal
35
1
0
05 Jun 2024
Mixup Augmentation with Multiple Interpolations
Mixup Augmentation with Multiple Interpolations
Lifeng Shen
Jincheng Yu
Hansi Yang
James T. Kwok
36
0
0
03 Jun 2024
Differentially Private Fine-Tuning of Diffusion Models
Differentially Private Fine-Tuning of Diffusion Models
Yu-Lin Tsai
Yizhe Li
Zekai Chen
Po-yu Chen
Chia-Mu Yu
Xuebin Ren
Francois Buet-Golfouse
60
3
0
03 Jun 2024
Robust Classification by Coupling Data Mollification with Label Smoothing
Robust Classification by Coupling Data Mollification with Label Smoothing
Markus Heinonen
Ba-Hien Tran
Michael Kampffmeyer
Maurizio Filippone
73
0
0
03 Jun 2024
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial
  Training
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
Jiacheng Zhang
Feng Liu
Dawei Zhou
Jingfeng Zhang
Tongliang Liu
AAML
51
2
0
02 Jun 2024
On the Use of Anchoring for Training Vision Models
On the Use of Anchoring for Training Vision Models
V. Narayanaswamy
Kowshik Thopalli
Rushil Anirudh
Yamen Mubarka
W. Sakla
Jayaraman J. Thiagarajan
52
0
0
01 Jun 2024
Robust Knowledge Distillation Based on Feature Variance Against
  Backdoored Teacher Model
Robust Knowledge Distillation Based on Feature Variance Against Backdoored Teacher Model
Jinyin Chen
Xiaoming Zhao
Haibin Zheng
Xiao Li
Sheng Xiang
Haifeng Guo
AAML
32
3
0
01 Jun 2024
StyDeSty: Min-Max Stylization and Destylization for Single Domain
  Generalization
StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization
Songhua Liu
Xin Jin
Xingyi Yang
Jingwen Ye
Xinchao Wang
OOD
59
1
0
01 Jun 2024
einspace: Searching for Neural Architectures from Fundamental Operations
einspace: Searching for Neural Architectures from Fundamental Operations
Linus Ericsson
Miguel Espinosa
Chenhongyi Yang
Antreas Antoniou
Amos Storkey
Shay B. Cohen
Jingyu Sun
Elliot J. Crowley
40
1
0
31 May 2024
Improving Generalization and Convergence by Enhancing Implicit
  Regularization
Improving Generalization and Convergence by Enhancing Implicit Regularization
Mingze Wang
Haotian He
Jinbo Wang
Zilin Wang
Guanhua Huang
Feiyu Xiong
Zhiyu Li
E. Weinan
Lei Wu
54
7
0
31 May 2024
Generalized Semi-Supervised Learning via Self-Supervised Feature
  Adaptation
Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation
Jiachen Liang
Ruibing Hou
Hong Chang
Bingpeng Ma
Shiguang Shan
Xilin Chen
44
4
0
31 May 2024
Knockout: A simple way to handle missing inputs
Knockout: A simple way to handle missing inputs
Minh Nguyen
Batuhan K. Karaman
Heejong Kim
Alan Q. Wang
Fengbei Liu
M. Sabuncu
OOD
UQCV
39
2
0
30 May 2024
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu
Tong Bu
Jianhao Ding
Zecheng Hao
Tiejun Huang
Zhaofei Yu
AAML
44
4
0
30 May 2024
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided
  by a Function Prior
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
Shuyu Cheng
Yibo Miao
Yinpeng Dong
Xiao Yang
Xiao-Shan Gao
Jun Zhu
AAML
39
3
0
29 May 2024
Federated Learning under Partially Class-Disjoint Data via Manifold
  Reshaping
Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping
Ziqing Fan
Jiangchao Yao
Ruipeng Zhang
Lingjuan Lyu
Ya Zhang
Yanfeng Wang
FedML
32
2
0
29 May 2024
MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under
  Distribution Shifts
MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
Renchunzi Xie
Ambroise Odonnat
Vasilii Feofanov
Weijian Deng
Jianfeng Zhang
Bo An
61
2
0
29 May 2024
Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active
  Learning and Model Selection
Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection
Yushu Li
Yongyi Su
Xulei Yang
Kui Jia
Xun Xu
TTA
38
0
0
29 May 2024
A Causal Framework for Evaluating Deferring Systems
A Causal Framework for Evaluating Deferring Systems
Filippo Palomba
Andrea Pugnana
Jose M. Alvarez
Salvatore Ruggieri
CML
59
3
0
29 May 2024
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