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OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?

3 October 2024

Papers citing "OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?"

46 / 46 papers shown

Title
Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations GuanWen Qiu Da Kuang Surbhi Goel 74 8 0 05 Mar 2024
Unraveling the Key Components of OOD Generalization via Diversification Harold Benoit Liangze Jiang Andrei Atanov Ouguzhan Fatih Kar Mattia Rigotti Amir Zamir CML 62 2 0 26 Dec 2023
On the Foundations of Shortcut Learning Katherine Hermann Hossein Mobahi Thomas Fel M. C. Mozer VLM 84 32 0 24 Oct 2023
Challenges and Opportunities in Improving Worst-Group Generalization in Presence of Spurious Features S. Joshi Yu Yang Yihao Xue Wenhan Yang Baharan Mirzasoleiman 74 13 0 21 Jun 2023
On the Joint Interaction of Models, Data, and Features Yiding Jiang Christina Baek J. Zico Kolter FedML 46 4 0 07 Jun 2023
Model Spider: Learning to Rank Pre-Trained Models Efficiently Yi-Kai Zhang Ting Huang Yao-Xiang Ding De-Chuan Zhan Han-Jia Ye 92 28 0 06 Jun 2023
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How Sebastian Pineda Arango Fabio Ferreira Arlind Kadra Frank Hutter Frank Hutter Josif Grabocka 73 16 0 06 Jun 2023
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization Yebin Liu Chris Xing Tian Haoliang Li Lei Ma Shiqi Wang UQCV 75 21 0 05 Jun 2023
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias Yu Yang Eric Gan Gintare Karolina Dziugaite Baharan Mirzasoleiman 52 28 0 30 May 2023
Characterizing Out-of-Distribution Error via Optimal Transport Yuzhe Lu Yilong Qin Runtian Zhai Andrew Shen Ketong Chen Zhenlin Wang Soheil Kolouri Simon Stepputtis Joseph Campbell Katia Sycara OODD 71 11 0 25 May 2023
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning Micah Goldblum Marc Finzi K. Rowan A. Wilson UQCV FedML 91 43 0 11 Apr 2023
Change is Hard: A Closer Look at Subpopulation Shift Yuzhe Yang Haoran Zhang Dina Katabi Marzyeh Ghassemi OOD 58 107 0 23 Feb 2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien A. Cabannes B. Kiani Randall Balestriero Yann LeCun A. Bietti SSL 75 33 0 06 Feb 2023
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets Damien Teney Yong Lin Seong Joon Oh Ehsan Abbasnejad OOD 512 50 0 01 Sep 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 88 29 0 06 Jul 2022
When Does Group Invariant Learning Survive Spurious Correlations? Yimeng Chen Ruibin Xiong Zhiming Ma Yanyan Lan OOD CML 79 22 0 29 Jun 2022
Zero-Shot AutoML with Pretrained Models Ekrem Öztürk Fabio Ferreira H. Jomaa Lars Schmidt-Thieme Josif Grabocka Frank Hutter VLM 90 10 0 16 Jun 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
ZIN: When and How to Learn Invariance Without Environment Partition? Yong Lin Shengyu Zhu Lu Tan Peng Cui OOD CML 63 69 0 11 Mar 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 883 13,148 0 04 Mar 2022
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts Weixin Liang James Zou OOD 79 84 0 14 Feb 2022
Agree to Disagree: Diversity through Disagreement for Better Transferability Matteo Pagliardini Martin Jaggi Franccois Fleuret Sai Praneeth Karimireddy 66 75 0 09 Feb 2022
Diversify and Disambiguate: Learning From Underspecified Data Yoonho Lee Huaxiu Yao Chelsea Finn 263 66 0 07 Feb 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton Behnam Neyshabur Hanie Sedghi OODD OOD 67 131 0 11 Jan 2022
Simple data balancing achieves competitive worst-group-accuracy Badr Youbi Idrissi Martín Arjovsky Mohammad Pezeshki David Lopez-Paz 115 182 0 27 Oct 2021
A Fine-Grained Analysis on Distribution Shift Olivia Wiles Sven Gowal Florian Stimberg Sylvestre-Alvise Rebuffi Ira Ktena Krishnamurthy Dvijotham A. Cemgil OOD 291 213 0 21 Oct 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 149 535 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 97 562 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 80 278 0 09 Jul 2021
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization Nanyang Ye Kaican Li Haoyue Bai Runpeng Yu Lanqing Hong Fengwei Zhou Zhenguo Li Jun Zhu CML OOD 78 109 0 07 Jun 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 967 29,731 0 26 Feb 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 191 1,445 0 14 Dec 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 80 252 0 25 Nov 2020
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 117 688 0 06 Nov 2020
Understanding the Failure Modes of Out-of-Distribution Generalization Vaishnavh Nagarajan Anders Andreassen Behnam Neyshabur OOD OODD 61 177 0 29 Oct 2020
In Search of Lost Domain Generalization Ishaan Gulrajani David Lopez-Paz OOD 91 1,156 0 02 Jul 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 393 1,987 0 11 Apr 2020
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging Luke Oakden-Rayner Jared A. Dunnmon G. Carneiro Christopher Ré OOD 73 384 0 27 Sep 2019
AutoML: A Survey of the State-of-the-Art Xin He Kaiyong Zhao Xiaowen Chu 132 1,457 0 02 Aug 2019
Dataset2Vec: Learning Dataset Meta-Features H. Jomaa Lars Schmidt-Thieme Josif Grabocka SSL 84 62 0 27 May 2019
Task2Vec: Task Embedding for Meta-Learning Alessandro Achille Michael Lam Rahul Tewari Avinash Ravichandran Subhransu Maji Charless C. Fowlkes Stefano Soatto Pietro Perona SSL 77 315 0 10 Feb 2019
Automated Algorithm Selection: Survey and Perspectives P. Kerschke Holger H. Hoos Frank Neumann Heike Trautmann 48 382 0 28 Nov 2018
Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning S. Raschka 124 783 0 13 Nov 2018
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,322 0 10 Dec 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,424 0 28 Nov 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 422 43,777 0 01 May 2014