Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms

2 November 2023

Haoxiang Wang

Gargi Balasubramaniam

Papers citing "Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms"

45 / 45 papers shown

Title
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems Mao Ye Ruichen Jiang Haoxiang Wang Dhruv Choudhary Xiaocong Du Bhargav Bhushanam Aryan Mokhtari A. Kejariwal Qiang Liu TTA OOD AI4TS 72 8 0 02 Sep 2022
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond Haoxiang Wang Yue Liu Han Zhao OOD CLL 60 39 0 18 Apr 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 86 339 0 06 Apr 2022
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution Ananya Kumar Aditi Raghunathan Robbie Jones Tengyu Ma Percy Liang OODD 126 683 0 21 Feb 2022
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 71 82 0 14 Feb 2022
Salient ImageNet: How to discover spurious features in Deep Learning? Sahil Singla Soheil Feizi AAML VLM 84 120 0 08 Oct 2021
Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles Xin Du S. Ramamoorthy W. Duivesteijn Jin Tian Mykola Pechenizkiy 58 3 0 21 Sep 2021
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 154 736 0 04 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 155 535 0 31 Aug 2021
Just Train Twice: Improving Group Robustness without Training Group Information Emmy Liu Behzad Haghgoo Annie S. Chen Aditi Raghunathan Pang Wei Koh Shiori Sagawa Percy Liang Chelsea Finn OOD 102 562 0 19 Jul 2021
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization John Miller Rohan Taori Aditi Raghunathan Shiori Sagawa Pang Wei Koh Vaishaal Shankar Percy Liang Y. Carmon Ludwig Schmidt OODD OOD 94 278 0 09 Jul 2021
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments Yining Chen Elan Rosenfeld Mark Sellke Tengyu Ma Andrej Risteski OOD 66 33 0 18 Jun 2021
On Invariance Penalties for Risk Minimization Kia Khezeli Arno Blaas Frank Soboczenski N. Chia John Kalantari 51 16 0 17 Jun 2021
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation Haoxiang Wang Han Zhao Yue Liu 95 90 0 16 Jun 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja Ethan Caballero Dinghuai Zhang Jean-Christophe Gagnon-Audet Yoshua Bengio Ioannis Mitliagkas Irina Rish OOD 62 269 0 11 Jun 2021
Invariant Information Bottleneck for Domain Generalization Yue Liu Yifei Shen Yezhen Wang Wenzhen Zhu Colorado Reed Jun Zhang Dongsheng Li Kurt Keutzer Han Zhao OOD 76 115 0 11 Jun 2021
Towards a Theoretical Framework of Out-of-Distribution Generalization Haotian Ye Chuanlong Xie Tianle Cai Ruichen Li Zhenguo Li Liwei Wang OODD OOD 100 112 0 08 Jun 2021
Domain Generalization: A Survey Kaiyang Zhou Ziwei Liu Yu Qiao Tao Xiang Chen Change Loy OOD AI4CE 254 1,019 0 03 Mar 2021
Generalizing to Unseen Domains: A Survey on Domain Generalization Jindong Wang Cuiling Lan Chang-Shu Liu Yidong Ouyang Tao Qin Wang Lu Yiqiang Chen Wenjun Zeng Philip S. Yu OOD 221 1,230 0 02 Mar 2021
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 268 128 0 04 Jan 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 227 1,445 0 14 Dec 2020
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective Kartik Ahuja Jun Wang Amit Dhurandhar Karthikeyan Shanmugam Kush R. Varshney OOD 83 79 0 30 Oct 2020
The Risks of Invariant Risk Minimization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 88 312 0 12 Oct 2020
Learning explanations that are hard to vary Giambattista Parascandolo Alexander Neitz Antonio Orvieto Luigi Gresele Bernhard Schölkopf FAtt 71 187 0 01 Sep 2020
In Search of Lost Domain Generalization Ishaan Gulrajani David Lopez-Paz OOD 91 1,156 0 02 Jul 2020
Learning Causal Models Online Khurram Javed Martha White Yoshua Bengio CML 53 33 0 12 Jun 2020
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift Rémi Tachet des Combes Han Zhao Yu Wang Geoffrey J. Gordon OOD AAML VLM 76 190 0 10 Mar 2020
Invariant Risk Minimization Games Kartik Ahuja Karthikeyan Shanmugam Kush R. Varshney Amit Dhurandhar OOD 74 251 0 11 Feb 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 108 1,248 0 20 Nov 2019
Generalizing to unseen domains via distribution matching Isabela Albuquerque João Monteiro Mohammad Javad Darvishi Bayazi T. Falk Ioannis Mitliagkas OOD 79 157 0 03 Nov 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 195 2,242 0 05 Jul 2019
Recognition in Terra Incognita Sara Beery Grant Van Horn Pietro Perona 97 853 0 13 Jul 2018
Generalizing to Unseen Domains via Adversarial Data Augmentation Riccardo Volpi Hongseok Namkoong Ozan Sener John C. Duchi Vittorio Murino Silvio Savarese OOD 122 786 0 30 May 2018
Annotation Artifacts in Natural Language Inference Data Suchin Gururangan Swabha Swayamdipta Omer Levy Roy Schwartz Samuel R. Bowman Noah A. Smith 155 1,180 0 06 Mar 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 199 783 0 14 Nov 2017
CyCADA: Cycle-Consistent Adversarial Domain Adaptation Judy Hoffman Eric Tzeng Taesung Park Jun-Yan Zhu Phillip Isola Kate Saenko Alexei A. Efros Trevor Darrell 147 3,005 0 08 Nov 2017
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference Adina Williams Nikita Nangia Samuel R. Bowman 524 4,494 0 18 Apr 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 829 11,943 0 09 Mar 2017
Adversarial Discriminative Domain Adaptation Eric Tzeng Judy Hoffman Kate Saenko Trevor Darrell GAN OOD 270 4,673 0 17 Feb 2017
Deep CORAL: Correlation Alignment for Deep Domain Adaptation Baochen Sun Kate Saenko OOD 105 3,165 0 06 Jul 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 390 9,515 0 28 May 2015
Learning Transferable Features with Deep Adaptation Networks Mingsheng Long Yue Cao Jianmin Wang Michael I. Jordan OOD 223 5,211 0 10 Feb 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 124 973 0 06 Jan 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,426 0 28 Nov 2014
Domain Generalization via Invariant Feature Representation Krikamol Muandet David Balduzzi Bernhard Schölkopf OOD 142 1,188 0 10 Jan 2013