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Learning Robust Global Representations by Penalizing Local Predictive
  Power
v1v2 (latest)

Learning Robust Global Representations by Penalizing Local Predictive Power

Neural Information Processing Systems (NeurIPS), 2019
29 May 2019
Haohan Wang
Songwei Ge
Eric Xing
Zachary Chase Lipton
    OOD
ArXiv (abs)PDFHTML

Papers citing "Learning Robust Global Representations by Penalizing Local Predictive Power"

50 / 818 papers shown
Toward Learning Human-aligned Cross-domain Robust Models by Countering
  Misaligned Features
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features
Haohan Wang
Zeyi Huang
Hanlin Zhang
Yong Jae Lee
Eric P. Xing
OOD
375
16
0
05 Nov 2021
Robust Contrastive Learning Using Negative Samples with Diminished
  Semantics
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
Songwei Ge
Shlok Kumar Mishra
Haohan Wang
Chun-Liang Li
David Jacobs
SSL
193
76
0
27 Oct 2021
AugMax: Adversarial Composition of Random Augmentations for Robust
  Training
AugMax: Adversarial Composition of Random Augmentations for Robust Training
Haotao Wang
Chaowei Xiao
Jean Kossaifi
Zhiding Yu
Anima Anandkumar
Zinan Lin
333
132
0
26 Oct 2021
Unrestricted Adversarial Attacks on ImageNet Competition
Unrestricted Adversarial Attacks on ImageNet Competition
YueFeng Chen
Xiaofeng Mao
Yuan He
Hui Xue
Chao Li
...
Bingyang Fu
Yunfei Zheng
Yekui Wang
Haorong Luo
Zhen Yang
AAML
152
13
0
17 Oct 2021
Combining Diverse Feature Priors
Combining Diverse Feature Priors
Saachi Jain
Dimitris Tsipras
Aleksander Madry
246
15
0
15 Oct 2021
Reappraising Domain Generalization in Neural Networks
Reappraising Domain Generalization in Neural Networks
S. Sivaprasad
Akshay Goindani
Vaibhav Garg
Ritam Basu
Saiteja Kosgi
Vineet Gandhi
OODAI4CE
264
6
0
15 Oct 2021
CLIP-Adapter: Better Vision-Language Models with Feature Adapters
CLIP-Adapter: Better Vision-Language Models with Feature AdaptersInternational Journal of Computer Vision (IJCV), 2021
Shiyang Feng
Shijie Geng
Renrui Zhang
Teli Ma
Rongyao Fang
Zelong Li
Jiaming Song
Yu Qiao
VLMCLIP
1.2K
1,431
0
09 Oct 2021
Cycle-Consistent World Models for Domain Independent Latent Imagination
Cycle-Consistent World Models for Domain Independent Latent Imagination
Sidney Bender
Tim Joseph
Marius Zoellner
242
0
0
02 Oct 2021
Shape-Biased Domain Generalization via Shock Graph Embeddings
Shape-Biased Domain Generalization via Shock Graph Embeddings
M. Narayanan
Vickram Rajendran
Benjamin Kimia
147
15
0
13 Sep 2021
Robust fine-tuning of zero-shot models
Robust fine-tuning of zero-shot models
Mitchell Wortsman
Gabriel Ilharco
Jong Wook Kim
Mike Li
Simon Kornblith
...
Raphael Gontijo-Lopes
Hannaneh Hajishirzi
Ali Farhadi
Hongseok Namkoong
Ludwig Schmidt
VLM
635
896
0
04 Sep 2021
Learning to Prompt for Vision-Language Models
Learning to Prompt for Vision-Language Models
Kaiyang Zhou
Jingkang Yang
Chen Change Loy
Ziwei Liu
VPVLMCLIPVLM
1.3K
3,323
0
02 Sep 2021
On-target Adaptation
On-target Adaptation
Yi Xu
Shaoteng Liu
Sayna Ebrahimi
Evan Shelhamer
Trevor Darrell
TTA
228
20
0
02 Sep 2021
Learning to Diversify for Single Domain Generalization
Learning to Diversify for Single Domain GeneralizationIEEE International Conference on Computer Vision (ICCV), 2021
Zijian Wang
Yadan Luo
Ruihong Qiu
Zi Huang
Mahsa Baktash
392
314
0
26 Aug 2021
Discovering Spatial Relationships by Transformers for Domain
  Generalization
Discovering Spatial Relationships by Transformers for Domain Generalization
Cuicui Kang
Karthik Nandakumar
ViT
177
1
0
23 Aug 2021
Exploring Data Aggregation and Transformations to Generalize across
  Visual Domains
Exploring Data Aggregation and Transformations to Generalize across Visual Domains
Antono DÍnnocente
OOD
184
0
0
20 Aug 2021
Feature Stylization and Domain-aware Contrastive Learning for Domain
  Generalization
Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization
Seogkyu Jeon
Kibeom Hong
Pilhyeon Lee
Jewook Lee
H. Byun
OOD
223
90
0
19 Aug 2021
Out-of-Domain Generalization from a Single Source: An Uncertainty
  Quantification Approach
Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification ApproachIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Xi Peng
Fengchun Qiao
Long Zhao
OOD
357
45
0
05 Aug 2021
Object-aware Contrastive Learning for Debiased Scene Representation
Object-aware Contrastive Learning for Debiased Scene RepresentationNeural Information Processing Systems (NeurIPS), 2021
Sangwoo Mo
H. Kang
Kihyuk Sohn
Chun-Liang Li
Jinwoo Shin
SSLOCL
292
54
0
30 Jul 2021
Using Synthetic Corruptions to Measure Robustness to Natural
  Distribution Shifts
Using Synthetic Corruptions to Measure Robustness to Natural Distribution ShiftsBritish Machine Vision Conference (BMVC), 2021
Alfred Laugros
A. Caplier
Matthieu Ospici
142
7
0
26 Jul 2021
Predicting with Confidence on Unseen Distributions
Predicting with Confidence on Unseen Distributions
Devin Guillory
Vaishaal Shankar
Sayna Ebrahimi
Trevor Darrell
Ludwig Schmidt
UQCVOOD
286
138
0
07 Jul 2021
Learning Task Informed Abstractions
Learning Task Informed AbstractionsInternational Conference on Machine Learning (ICML), 2021
Xiang Fu
Ge Yang
Pulkit Agrawal
Tommi Jaakkola
291
74
0
29 Jun 2021
Partial success in closing the gap between human and machine vision
Partial success in closing the gap between human and machine visionNeural Information Processing Systems (NeurIPS), 2021
Robert Geirhos
Kantharaju Narayanappa
Benjamin Mitzkus
Tizian Thieringer
Matthias Bethge
Felix Wichmann
Wieland Brendel
VLMAAML
325
267
0
14 Jun 2021
Gradual Domain Adaptation in the Wild:When Intermediate Distributions
  are Absent
Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent
Samira Abnar
Rianne van den Berg
Golnaz Ghiasi
Mostafa Dehghani
Nal Kalchbrenner
Hanie Sedghi
OODCLLTTA
216
27
0
10 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in
  Federated Learning
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated LearningComputer Vision and Pattern Recognition (CVPR), 2021
Liangqiong Qu
Yuyin Zhou
Paul Pu Liang
Yingda Xia
Feifei Wang
Ehsan Adeli
L. Fei-Fei
D. Rubin
FedMLAI4CE
402
214
0
10 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and PrimerACM Computing Surveys (CSUR), 2021
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zinan Lin
J. Yadawa
313
45
0
09 Jun 2021
Frustratingly Easy Uncertainty Estimation for Distribution Shift
Frustratingly Easy Uncertainty Estimation for Distribution Shift
Tiago Salvador
Vikram S. Voleti
Alexander Iannantuono
Adam M. Oberman
OODUQCV
197
1
0
07 Jun 2021
OoD-Bench: Quantifying and Understanding Two Dimensions of
  Out-of-Distribution Generalization
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution GeneralizationComputer Vision and Pattern Recognition (CVPR), 2021
Nanyang Ye
Kaican Li
Haoyue Bai
Runpeng Yu
Lanqing Hong
Fengwei Zhou
Zhenguo Li
Jun Zhu
CMLOOD
286
129
0
07 Jun 2021
Personalizing Pre-trained Models
Personalizing Pre-trained Models
Mina Khan
P. Srivatsa
Advait Rane
Shriram Chenniappa
A. Hazariwala
Pattie Maes
VLM
201
7
0
02 Jun 2021
Towards Robust Vision Transformer
Towards Robust Vision TransformerComputer Vision and Pattern Recognition (CVPR), 2021
Xiaofeng Mao
Gege Qi
YueFeng Chen
Xiaodan Li
Ranjie Duan
Shaokai Ye
Yuan He
Hui Xue
ViT
430
232
0
17 May 2021
If your data distribution shifts, use self-learning
If your data distribution shifts, use self-learning
E. Rusak
Steffen Schneider
George Pachitariu
L. Eck
Peter V. Gehler
Oliver Bringmann
Wieland Brendel
Matthias Bethge
VLMOODTTA
430
36
0
27 Apr 2021
Does enhanced shape bias improve neural network robustness to common
  corruptions?
Does enhanced shape bias improve neural network robustness to common corruptions?International Conference on Learning Representations (ICLR), 2021
Chaithanya Kumar Mummadi
Ranjitha Subramaniam
Robin Hutmacher
Julien Vitay
Volker Fischer
J. H. Metzen
196
43
0
20 Apr 2021
Open Domain Generalization with Domain-Augmented Meta-Learning
Open Domain Generalization with Domain-Augmented Meta-LearningComputer Vision and Pattern Recognition (CVPR), 2021
Yang Shu
Zhangjie Cao
Chenyu Wang
Jianmin Wang
Mingsheng Long
OOD
167
172
0
08 Apr 2021
A Broad Study on the Transferability of Visual Representations with
  Contrastive Learning
A Broad Study on the Transferability of Visual Representations with Contrastive LearningIEEE International Conference on Computer Vision (ICCV), 2021
Ashraful Islam
Chun-Fu Chen
Yikang Shen
Leonid Karlinsky
Richard J. Radke
Rogerio Feris
SSL
319
129
0
24 Mar 2021
Can Targeted Adversarial Examples Transfer When the Source and Target
  Models Have No Label Space Overlap?
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?
Nathan Inkawhich
Kevin J. Liang
Jingyang Zhang
Huanrui Yang
Xue Yang
Yiran Chen
AAML
114
5
0
17 Mar 2021
Uncertainty-guided Model Generalization to Unseen Domains
Uncertainty-guided Model Generalization to Unseen DomainsComputer Vision and Pattern Recognition (CVPR), 2021
Fengchun Qiao
Xi Peng
OODUQCV
226
71
0
12 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language SupervisionInternational Conference on Machine Learning (ICML), 2021
Alec Radford
Jong Wook Kim
Chris Hallacy
Aditya A. Ramesh
Gabriel Goh
...
Amanda Askell
Pamela Mishkin
Jack Clark
Gretchen Krueger
Ilya Sutskever
CLIPVLM
2.0K
41,259
0
26 Feb 2021
Rethinking Domain Generalization Baselines
Rethinking Domain Generalization BaselinesInternational Conference on Pattern Recognition (ICPR), 2021
Francesco Cappio Borlino
A. DÍnnocente
Tatiana Tommasi
OOD
262
44
0
22 Jan 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution ShiftsInternational Conference on Machine Learning (ICML), 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Abigail Z. Jacobs
OOD
672
1,653
0
14 Dec 2020
Squared $\ell_2$ Norm as Consistency Loss for Leveraging Augmented Data
  to Learn Robust and Invariant Representations
Squared ℓ2\ell_2ℓ2​ Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations
Haohan Wang
Zeyi Huang
Xindi Wu
Eric Xing
149
2
0
25 Nov 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained
  Classification Problems
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification ProblemsNeural Information Processing Systems (NeurIPS), 2020
N. Sohoni
Jared A. Dunnmon
Geoffrey Angus
Albert Gu
Christopher Ré
277
278
0
25 Nov 2020
Creative Sketch Generation
Creative Sketch GenerationInternational Conference on Learning Representations (ICLR), 2020
Songwei Ge
Vedanuj Goswami
C. L. Zitnick
Devi Parikh
283
87
0
19 Nov 2020
Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles
Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles
Christopher Clark
Mark Yatskar
Luke Zettlemoyer
217
63
0
07 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine
  Learning
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
...
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
OffRL
428
764
0
06 Nov 2020
Learning Visual Representations for Transfer Learning by Suppressing
  Texture
Learning Visual Representations for Transfer Learning by Suppressing Texture
Shlok Kumar Mishra
Anshul B. Shah
Ankan Bansal
Janit Anjaria
Jonghyun Choi
Abhinav Shrivastava
Abhishek Sharma
David Jacobs
SSL
457
14
0
03 Nov 2020
Why Do Better Loss Functions Lead to Less Transferable Features?
Why Do Better Loss Functions Lead to Less Transferable Features?Neural Information Processing Systems (NeurIPS), 2020
Simon Kornblith
Ting-Li Chen
Honglak Lee
Mohammad Norouzi
FaML
286
103
0
30 Oct 2020
Maximum-Entropy Adversarial Data Augmentation for Improved
  Generalization and Robustness
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Long Zhao
Ting Liu
Xi Peng
Dimitris N. Metaxas
OODAAML
424
184
0
15 Oct 2020
Representation Learning via Invariant Causal Mechanisms
Representation Learning via Invariant Causal Mechanisms
Jovana Mitrović
Brian McWilliams
Jacob Walker
Lars Buesing
Charles Blundell
CMLOODSSL
212
276
0
15 Oct 2020
Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image
  Classification
Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image ClassificationComputer Vision and Pattern Recognition (CVPR), 2020
Oren Nuriel
Sagie Benaim
Lior Wolf
250
109
0
09 Oct 2020
Encoding Robustness to Image Style via Adversarial Feature Perturbations
Encoding Robustness to Image Style via Adversarial Feature PerturbationsNeural Information Processing Systems (NeurIPS), 2020
Manli Shu
Zuxuan Wu
Micah Goldblum
Tom Goldstein
AAMLOOD
190
22
0
18 Sep 2020
Delving Deeper into Anti-aliasing in ConvNets
Delving Deeper into Anti-aliasing in ConvNets
Xueyan Zou
Fanyi Xiao
Zhiding Yu
Yong Jae Lee
SupR
232
129
0
21 Aug 2020
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