Accepted Papers
Simple and near-optimal algorithms for hidden stratification and multi-group learning. Tosh, Christopher J; Hsu, Daniel J
GAPX: Generalized Autoregressive Paraphrase-Identification X. Zhou, Yifei; Li, Renyu; Housen, Hayden; Lim, Ser-Nam
Generative Gradual Domain Adaptation with Optimal Transport. He, Yifei; Wang, Haoxiang; Zhao, Han
Pareto Invariant Risk Minimization. Chen, Yongqiang; Zhou, Kaiwen; Bian, Yatao; Xie, Binghui; Ma, Kaili; Zhang, Yonggang; Yang, Han; Han, Bo; Cheng, James
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation. Zadorozhny, Karina; Thoral, Patrick; Elbers, Paul; Cinà, Giovanni
Distribution Shift nested in Web Scraping : Adapting MS COCO for Inclusive Data. Bayet, Theophile; Denis, Christophe; Zucker, Jean-Daniel; BAH, Alassane
Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction. Lu, Charles; Ahmed, Syed Rakin; Singh, Praveer; Kalpathy-Cramer, Jayashree
ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise. Ko, Jongwoo; Yi, Bongsoo; Yun, Se-Young
Diversify and Disambiguate: Learning from Underspecified Data. Lee, Yoonho; Yao, Huaxiu; Finn, Chelsea
Back to the Basics: Revisiting Out-of-Distribution Detection Baselines. Kuan, Johnson; Mueller, Jonas
Style Balancing and Test-Time Style Shifting for Domain Generalization. Park, Jungwuk; Han, Dong-Jun; Kim, Soyeong; Moon, Jaekyun
Models Out of Line: A Fourier Lens on Distribution Shift Robustness. Fridovich-Keil, Sara; Bartoldson, Brian R; Diffenderfer, James; Kailkhura, Bhavya; Bremer, Peer-Timo
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening. Gonzalez, Martin; Hajri, Hatem; Cantat, Loic; Petreczky, Mihaly
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift. Wu, Jingfeng; Zou, Difan; Braverman, Vladimir; Gu, Quanquan; Kakade, Sham
A Bias-Variance Analysis of Weight Averaging for OOD Generalization. Ramé, Alexandre; Kirchmeyer, Matthieu; Rahier, Thibaud; Rakotomamonjy, Alain; Gallinari, Patrick; Cord, Matthieu
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization. LeJeune, Daniel; Liu, Jiayu; Heckel, Reinhard
What You See is What You Get: Distributional Generalization for Algorithm Design in Deep Learning. Kulynych, Bogdan; Yang, Yao-Yuan; Yu, Yaodong; Błasiok, Jarosław; Nakkiran, Preetum
Time Series Prediction under Distribution Shift using Differentiable Forgetting. Bennett, Stefanos; Clarkson, Jason O
On the nonlinear correlation of ML performance across data subpopulations. Liang, Weixin; Mao, Yining; Kwon, Yongchan; Yang, Xinyu; Zou, James
Data Augmentation vs. Equivariant Networks: A Theoretical Study of Generalizability on Dynamics Forecasting. Wang, Rui; Walters, Robin; Yu, Rose
Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee. Nemmour, Yassine; Kremer, Heiner; Schölkopf, Bernhard; Zhu, Jia-Jie
DAFT: Distilling Adversarially Fine-tuned teachers for OOD Robustness. Nasery, Anshul; Addepalli, Sravanti; Netrapalli, Praneeth; Jain, Prateek
Evaluation of Generative Unsupervised Domain Adaptation in the Absence of Target Labels. Qiu, Zeju; Chrysos, Grigorios; Tzoumas, Stratis
GraphTTA: Test Time Adaptation on Graph Neural Networks. Chen, Guanzi; Zhang, Jiying; Xiao, Xi; Li, Yang
Adversarial Cheap Talk. Lu, Christopher; Willi, Timon; Letcher, Alistair HP; Foerster, Jakob
Fairness and robustness in anti-causal prediction. Makar, Maggie; D'Amour, Alexander
Plex: Towards Reliability using Pretrained Large Model Extensions. Tran, Dustin; Kirsch, Andreas; Lakshminarayanan, Balaji; Hu, Huiyi; Phan, Du; Sculley, D; Snoek, Jasper; Liu, Jeremiah; Ren, Jie; van Amersfoort, Joost; Han, Kehang; Buchanan, Kelly; Murphy, Kevin; Collier, Mark; Dusenberry, Michael W; Band, Neil B; Thain, Nithum; Jenatton, Rodolphe; Rudner, Tim G. J.; Gal, Yarin; Nado, Zachary; Mariet, Zelda; Wang, Zi; Ghahramani, Zoubin
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables. Xu, Mengdi; Huang, Peide; Kumar, Visak; Qiu, Jielin; Fang, Chao; Lee, Kuan-Hui; Qi, Xuewei ; Lam, Henry; Li, Bo; ZHAO, DING
Task Modeling: A Multitask Approach for Improving Robustness to Group Shifts. Li, Dongyue; Nguyen, Huy; Zhang, Hongyang R
A Meta-Analysis of Distributionally Robust Models. Feuer, Benjamin; Joshi, Ameya; Hegde, Chinmay
On Feature Learning in the Presence of Spurious Correlations. Izmailov, Pavel; Kirichenko, Polina; Gruver, Nate; Wilson, Andrew Gordon Gordon
Deep ensemble diversity and robustness on classification tasks. Mariet, Zelda
Asymmetry Learning for Counterfactual-invariant Classification in OOD Tasks. Mouli, S Chandra; Ribeiro, Bruno
Robust Estimation of Laplacian Constrained Gaussian Graphical Models with Trimmed Non-convex Regularization. Vargas Vieyra, Mariana
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets. Thams, Nikolaj; Oberst, Michael; Sontag, David
Improved Medical Out-of-Distribution Detectors For Modality and Semantic Shifts. Narayanaswamy, Vivek; Mubarka, Yamen; Anirudh, Rushil; Rajan, Deepta; Spanias, Andreas; J. Thiagarajan, Jayaraman
AugLoss: A Robust, Reliable Methodology for Real-World Corruptions. Otstot, Kyle; Cava, John Kevin L; Sypherd, Tyler; Sankar, Lalitha
Context Shift from Test Benchmarks to Real-World Production Performance. Groh, Matt
Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety. Trivedi, Puja; Koutra, Danai; J. Thiagarajan, Jayaraman
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data. Kaur, Ramneet; Sridhar, Kaustubh; Park, Sangdon; Jha, Susmit; Roy, Anirban ; Sokolsky, Oleg; Lee, Insup
Diagnosing Model Performance Under Distribution Shift. Cai, Tiffany; Namkoong, Hongseok; Yadlowsky, Steve
Distributionally Adaptive Meta Reinforcement Learning. Ajay, Anurag; Ghosh, Dibya; Levine, Sergey; Agrawal, Pulkit; Gupta, Abhishek
2 CENTs on continual adaptation: replay & parameter buffers stabilize entropy minimization. Press, Ori; Schneider, Steffen; Kümmerer, Matthias; Bethge, Matthias
Towards Practicable Sequential Shift Detectors. Cobb, Oliver; Van Looveren, Arnaud
Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective. Bazhenov, Gleb; Ivanov, Sergey; Panov, Maxim; Zaytsev, Alexey; Burnaev, Evgeny
What can we do with just the model? A simple knowledge extraction framework. Paul, Sujoy; Khurana, Ansh; Aggarwal, Gaurav
Are We Viewing the Problem of Robust Generalisation through the Appropriate Lens? Omran, Mohamed; Schiele, Bernt
Adapting to Shifts in Latent Confounders using Observed Concepts and Proxies. Kusner, Matt J; Alabdulmohsin, Ibrahim; Pfohl, Stephen R; Salaudeen, Olawale E; Gretton, Arthur; Koyejo, Sanmi; Schrouff, Jessica; D'Amour, Alexander
Positive Unlabeled Contrastive Representation Learning. Acharya, Anish; Sanghavi, Sujay; Jing, Li; Bhushanam, Bhargav; Rabbat, Mike; Choudhary, Dhruv; Dhillon, Inderjit S.
Towards Domain Adversarial Methods to Mitigate Texture Bias. Kashyap, Dhruva ; Aithal, Sumukh K; C, Rakshith; Subramanyam, Natarajan
Dynamics of Dataset Bias and Robustness. Pradhan, Prabhu; Rawal, Ruchit
Bridging Distribution Shift in Imitation Learning via Taylor Expansions. Pfrommer, Daniel; Zhang, Thomas T.C.K.; Matni, Nikolai; Tu, Stephen
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift. Baek, Christina; Jiang, Yiding; Raghunathan, Aditi; Kolter, Zico