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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 / 820 papers shown
Toward Learning Robust and Invariant Representations with Alignment
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Toward Learning Robust and Invariant Representations with Alignment Regularization and Data AugmentationKnowledge Discovery and Data Mining (KDD), 2022
Haohan Wang
Zeyi Huang
Xindi Wu
Eric P. Xing
OOD
135
16
0
04 Jun 2022
Siamese Image Modeling for Self-Supervised Vision Representation
  Learning
Siamese Image Modeling for Self-Supervised Vision Representation LearningComputer Vision and Pattern Recognition (CVPR), 2022
Chenxin Tao
Xizhou Zhu
Weijie Su
Gao Huang
Bin Li
Jie Zhou
Yu Qiao
Xiaogang Wang
Jifeng Dai
SSL
301
107
0
02 Jun 2022
Optimizing Relevance Maps of Vision Transformers Improves Robustness
Optimizing Relevance Maps of Vision Transformers Improves RobustnessNeural Information Processing Systems (NeurIPS), 2022
Hila Chefer
Idan Schwartz
Lior Wolf
ViT
297
46
0
02 Jun 2022
Prefix Conditioning Unifies Language and Label Supervision
Prefix Conditioning Unifies Language and Label SupervisionComputer Vision and Pattern Recognition (CVPR), 2022
Kuniaki Saito
Kihyuk Sohn
Xinming Zhang
Chun-Liang Li
Chen-Yu Lee
Kate Saenko
Tomas Pfister
VLMCLIP
177
19
0
02 Jun 2022
CropMix: Sampling a Rich Input Distribution via Multi-Scale Cropping
CropMix: Sampling a Rich Input Distribution via Multi-Scale Cropping
Junlin Han
L. Petersson
Hongdong Li
Ian Reid
171
10
0
31 May 2022
Prompt-aligned Gradient for Prompt Tuning
Prompt-aligned Gradient for Prompt TuningIEEE International Conference on Computer Vision (ICCV), 2022
B. Zhu
Yulei Niu
Yucheng Han
Yuehua Wu
Hanwang Zhang
VLM
730
420
0
30 May 2022
SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
Feng Liang
Yangguang Li
Diana Marculescu
SSLTPMViT
295
28
0
28 May 2022
CyCLIP: Cyclic Contrastive Language-Image Pretraining
CyCLIP: Cyclic Contrastive Language-Image PretrainingNeural Information Processing Systems (NeurIPS), 2022
Shashank Goel
Hritik Bansal
S. Bhatia
Ryan Rossi
Vishwa Vinay
Aditya Grover
CLIPVLM
520
165
0
28 May 2022
Matryoshka Representation Learning
Matryoshka Representation LearningNeural Information Processing Systems (NeurIPS), 2022
Aditya Kusupati
Gantavya Bhatt
Aniket Rege
Matthew Wallingford
Aditya Sinha
...
William Howard-Snyder
Kaifeng Chen
Sham Kakade
Prateek Jain
Ali Farhadi
493
169
0
26 May 2022
Linear Connectivity Reveals Generalization Strategies
Linear Connectivity Reveals Generalization StrategiesInternational Conference on Learning Representations (ICLR), 2022
Jeevesh Juneja
Rachit Bansal
Kyunghyun Cho
João Sedoc
Naomi Saphra
855
55
0
24 May 2022
Supporting Vision-Language Model Inference with Confounder-pruning
  Knowledge Prompt
Supporting Vision-Language Model Inference with Confounder-pruning Knowledge Prompt
Jiangmeng Li
Wenyi Mo
Jingyao Wang
Fuchun Sun
Changwen Zheng
Hui Xiong
Ji-Rong Wen
VLM
229
0
0
23 May 2022
AutoLink: Self-supervised Learning of Human Skeletons and Object
  Outlines by Linking Keypoints
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking KeypointsNeural Information Processing Systems (NeurIPS), 2022
Xingzhe He
Bastian Wandt
Helge Rhodin
SSL3DH3DPC
681
24
0
21 May 2022
Learn2Weight: Parameter Adaptation against Similar-domain Adversarial
  Attacks
Learn2Weight: Parameter Adaptation against Similar-domain Adversarial AttacksInternational Conference on Computational Linguistics (COLING), 2022
Siddhartha Datta
AAML
268
5
0
15 May 2022
When does dough become a bagel? Analyzing the remaining mistakes on
  ImageNet
When does dough become a bagel? Analyzing the remaining mistakes on ImageNetNeural Information Processing Systems (NeurIPS), 2022
Vijay Vasudevan
Benjamin Caine
Raphael Gontijo-Lopes
Sara Fridovich-Keil
Rebecca Roelofs
VLMUQCV
206
69
0
09 May 2022
Sequencer: Deep LSTM for Image Classification
Sequencer: Deep LSTM for Image ClassificationNeural Information Processing Systems (NeurIPS), 2022
Yuki Tatsunami
Masato Taki
VLMViT
347
109
0
04 May 2022
CoCa: Contrastive Captioners are Image-Text Foundation Models
CoCa: Contrastive Captioners are Image-Text Foundation Models
Jiahui Yu
Zirui Wang
Vijay Vasudevan
Legg Yeung
Mojtaba Seyedhosseini
Yonghui Wu
VLMCLIPOffRL
700
1,608
0
04 May 2022
Data Determines Distributional Robustness in Contrastive Language Image
  Pre-training (CLIP)
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)International Conference on Machine Learning (ICML), 2022
Alex Fang
Gabriel Ilharco
Mitchell Wortsman
Yu Wan
Vaishaal Shankar
Achal Dave
Ludwig Schmidt
VLMOOD
400
177
0
03 May 2022
Causal Transportability for Visual Recognition
Causal Transportability for Visual RecognitionComputer Vision and Pattern Recognition (CVPR), 2022
Chengzhi Mao
K. Xia
James Wang
Hongya Wang
Junfeng Yang
Elias Bareinboim
Carl Vondrick
CMLOODBDL
281
40
0
26 Apr 2022
Visual Attention Emerges from Recurrent Sparse Reconstruction
Visual Attention Emerges from Recurrent Sparse ReconstructionInternational Conference on Machine Learning (ICML), 2022
Baifeng Shi
Ya-heng Song
Neel Joshi
Trevor Darrell
Xin Eric Wang
3DH
171
7
0
23 Apr 2022
iCAR: Bridging Image Classification and Image-text Alignment for Visual
  Recognition
iCAR: Bridging Image Classification and Image-text Alignment for Visual Recognition
Yixuan Wei
Yue Cao
Zheng Zhang
Zhuliang Yao
Zhenda Xie
Han Hu
B. Guo
VLM
127
12
0
22 Apr 2022
Masked Siamese Networks for Label-Efficient Learning
Masked Siamese Networks for Label-Efficient LearningEuropean Conference on Computer Vision (ECCV), 2022
Mahmoud Assran
Mathilde Caron
Ishan Misra
Piotr Bojanowski
Florian Bordes
Pascal Vincent
Armand Joulin
Michael G. Rabbat
Nicolas Ballas
SSL
330
380
0
14 Apr 2022
Clothes-Changing Person Re-identification with RGB Modality Only
Clothes-Changing Person Re-identification with RGB Modality OnlyComputer Vision and Pattern Recognition (CVPR), 2022
Xinqian Gu
Hong Chang
Bingpeng Ma
Shutao Bai
Shiguang Shan
Xilin Chen
206
236
0
14 Apr 2022
No Token Left Behind: Explainability-Aided Image Classification and
  Generation
No Token Left Behind: Explainability-Aided Image Classification and GenerationEuropean Conference on Computer Vision (ECCV), 2022
Roni Paiss
Hila Chefer
Lior Wolf
VLM
209
35
0
11 Apr 2022
The Two Dimensions of Worst-case Training and the Integrated Effect for
  Out-of-domain Generalization
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain GeneralizationComputer Vision and Pattern Recognition (CVPR), 2022
Zeyi Huang
Haohan Wang
Dong Huang
Yong Jae Lee
Eric P. Xing
242
29
0
09 Apr 2022
MultiMAE: Multi-modal Multi-task Masked Autoencoders
MultiMAE: Multi-modal Multi-task Masked AutoencodersEuropean Conference on Computer Vision (ECCV), 2022
Roman Bachmann
David Mizrahi
Andrei Atanov
Amir Zamir
427
349
0
04 Apr 2022
Improving Vision Transformers by Revisiting High-frequency Components
Improving Vision Transformers by Revisiting High-frequency ComponentsEuropean Conference on Computer Vision (ECCV), 2022
Jiawang Bai
Liuliang Yuan
Shutao Xia
Shuicheng Yan
Zhifeng Li
Wen Liu
ViT
325
119
0
03 Apr 2022
Generating High Fidelity Data from Low-density Regions using Diffusion
  Models
Generating High Fidelity Data from Low-density Regions using Diffusion ModelsComputer Vision and Pattern Recognition (CVPR), 2022
Vikash Sehwag
C. Hazirbas
Albert Gordo
Firat Ozgenel
Cristian Canton Ferrer
DiffM
287
82
0
31 Mar 2022
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series
Jean-Christophe Gagnon-Audet
Kartik Ahuja
Mohammad Javad Darvishi Bayazi
Pooneh Mousavi
G. Dumas
Irina Rish
OODCMLAI4TS
281
40
0
18 Mar 2022
Conditional Prompt Learning for Vision-Language Models
Conditional Prompt Learning for Vision-Language ModelsComputer Vision and Pattern Recognition (CVPR), 2022
Kaiyang Zhou
Jingkang Yang
Chen Change Loy
Ziwei Liu
VLMCLIPVPVLM
513
1,873
0
10 Mar 2022
Model soups: averaging weights of multiple fine-tuned models improves
  accuracy without increasing inference time
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timeInternational Conference on Machine Learning (ICML), 2022
Mitchell Wortsman
Gabriel Ilharco
S. Gadre
Rebecca Roelofs
Raphael Gontijo-Lopes
...
Hongseok Namkoong
Ali Farhadi
Y. Carmon
Simon Kornblith
Ludwig Schmidt
MoMe
728
1,298
1
10 Mar 2022
Geodesic Multi-Modal Mixup for Robust Fine-Tuning
Geodesic Multi-Modal Mixup for Robust Fine-TuningNeural Information Processing Systems (NeurIPS), 2022
Changdae Oh
Junhyuk So
Hoyoon Byun
Yongtaek Lim
Minchul Shin
Jong-June Jeon
Kyungwoo Song
457
39
0
08 Mar 2022
Global-Local Regularization Via Distributional Robustness
Global-Local Regularization Via Distributional RobustnessInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Hoang Phan
Trung Le
Trung-Nghia Phung
Tu Bui
Nhat Ho
Dinh Q. Phung
OOD
260
15
0
01 Mar 2022
Fine-Tuning can Distort Pretrained Features and Underperform
  Out-of-Distribution
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-DistributionInternational Conference on Learning Representations (ICLR), 2022
Ananya Kumar
Aditi Raghunathan
Robbie Jones
Tengyu Ma
Abigail Z. Jacobs
OODD
312
831
0
21 Feb 2022
Deconstructing Distributions: A Pointwise Framework of Learning
Deconstructing Distributions: A Pointwise Framework of LearningInternational Conference on Learning Representations (ICLR), 2022
Gal Kaplun
Nikhil Ghosh
Saurabh Garg
Boaz Barak
Preetum Nakkiran
OOD
214
24
0
20 Feb 2022
Vision Models Are More Robust And Fair When Pretrained On Uncurated
  Images Without Supervision
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Priya Goyal
Quentin Duval
Isaac Seessel
Mathilde Caron
Ishan Misra
Levent Sagun
Armand Joulin
Piotr Bojanowski
VLMSSL
413
122
0
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Transferability in Deep Learning: A Survey
Transferability in Deep Learning: A Survey
Junguang Jiang
Yang Shu
Jianmin Wang
Mingsheng Long
OOD
199
132
0
15 Jan 2022
Pushing the limits of self-supervised ResNets: Can we outperform
  supervised learning without labels on ImageNet?
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
Nenad Tomašev
Ioana Bica
Brian McWilliams
Lars Buesing
Razvan Pascanu
Charles Blundell
Jovana Mitrović
SSL
358
94
0
13 Jan 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance
Leveraging Unlabeled Data to Predict Out-of-Distribution PerformanceInternational Conference on Learning Representations (ICLR), 2022
Saurabh Garg
Sivaraman Balakrishnan
Zachary Chase Lipton
Behnam Neyshabur
Hanie Sedghi
OODDOOD
292
157
0
11 Jan 2022
A ConvNet for the 2020s
A ConvNet for the 2020sComputer Vision and Pattern Recognition (CVPR), 2022
Zhuang Liu
Hanzi Mao
Chaozheng Wu
Christoph Feichtenhofer
Trevor Darrell
Saining Xie
ViT
611
7,049
0
10 Jan 2022
Optimal Representations for Covariate Shift
Optimal Representations for Covariate ShiftInternational Conference on Learning Representations (ICLR), 2021
Yangjun Ruan
Yann Dubois
Chris J. Maddison
OOD
441
74
0
31 Dec 2021
Measure and Improve Robustness in NLP Models: A Survey
Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang
Haohan Wang
Diyi Yang
537
159
0
15 Dec 2021
Dilated convolution with learnable spacings
Dilated convolution with learnable spacings
Ismail Khalfaoui-Hassani
Thomas Pellegrini
T. Masquelier
261
47
0
07 Dec 2021
A Systematic Review of Robustness in Deep Learning for Computer Vision:
  Mind the gap?
A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?
Nathan G. Drenkow
Numair Sani
I. Shpitser
Mathias Unberath
249
95
0
01 Dec 2021
Revisiting the Transferability of Supervised Pretraining: an MLP
  Perspective
Revisiting the Transferability of Supervised Pretraining: an MLP Perspective
Yizhou Wang
Weizhen He
Feng Zhu
Mengwei He
Rui Zhao
Donglian Qi
Wanli Ouyang
334
60
0
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Task2Sim : Towards Effective Pre-training and Transfer from Synthetic
  Data
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data
Samarth Mishra
Yikang Shen
Cheng Perng Phoo
Chun-Fu Chen
Leonid Karlinsky
Kate Saenko
Venkatesh Saligrama
Rogerio Feris
406
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Pyramid Adversarial Training Improves ViT Performance
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Charles Herrmann
Kyle Sargent
Lu Jiang
Ramin Zabih
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ViT
279
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GPR1200: A Benchmark for General-Purpose Content-Based Image Retrieval
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159
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Discrete Representations Strengthen Vision Transformer Robustness
Discrete Representations Strengthen Vision Transformer RobustnessInternational Conference on Learning Representations (ICLR), 2021
Chengzhi Mao
Lu Jiang
Mostafa Dehghani
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Rahul Sukthankar
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ViT
303
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Combined Scaling for Zero-shot Transfer Learning
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Hieu H. Pham
Zihang Dai
Golnaz Ghiasi
Kenji Kawaguchi
Hanxiao Liu
...
Yi-Ting Chen
Minh-Thang Luong
Yonghui Wu
Mingxing Tan
Quoc V. Le
VLM
390
229
0
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Merging Models with Fisher-Weighted Averaging
Merging Models with Fisher-Weighted Averaging
Michael Matena
Colin Raffel
FedMLMoMe
546
529
0
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