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Marginal Singularity, and the Benefits of Labels in Covariate-Shift

5 March 2018

Papers citing "Marginal Singularity, and the Benefits of Labels in Covariate-Shift"

50 / 67 papers shown

Title
Computational Efficiency under Covariate Shift in Kernel Ridge Regression Andrea Della Vecchia Arnaud Mavakala Watusadisi Ernesto De Vito Lorenzo Rosasco 47 0 0 20 May 2025
Locally Private Nonparametric Contextual Multi-armed Bandits Yuheng Ma Feiyu Jiang Zifeng Zhao Hanfang Yang Y. Yu 116 0 0 11 Mar 2025
Conformal Prediction Under Generalized Covariate Shift with Posterior Drift Baozhen Wang Xingye Qiao 152 0 0 25 Feb 2025
Deep Transfer Learning: Model Framework and Error Analysis Yuling Jiao Huazhen Lin Yuchen Luo Jerry Zhijian Yang 114 1 0 12 Oct 2024
Shape-restricted transfer learning analysis for generalized linear regression model Stefan Langer Tao Yu Andreas Nürnberger Jing Qin 58 0 0 31 Jul 2024
Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints Arnab Auddy T. T. Cai Abhinav Chakraborty 95 1 0 28 Jun 2024
Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction Kulunu Dharmakeerthi Y. Hur Tengyuan Liang 67 0 0 22 Jun 2024
Efficient Discrepancy Testing for Learning with Distribution Shift Gautam Chandrasekaran Adam R. Klivans Vasilis Kontonis Konstantinos Stavropoulos Arsen Vasilyan 82 3 0 13 Jun 2024
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization Yihang Chen Fanghui Liu Taiji Suzuki Volkan Cevher 84 1 0 05 Jun 2024
An adaptive transfer learning perspective on classification in non-stationary environments Henry W J Reeve 86 0 0 28 May 2024
Understanding Forgetting in Continual Learning with Linear Regression Meng Ding Kaiyi Ji Di Wang Jinhui Xu CLL 145 10 0 27 May 2024
Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift Mitsuhiro Fujikawa Yohei Akimoto Jun Sakuma Kazuto Fukuchi 48 0 0 27 May 2024
Sharp analysis of out-of-distribution error for "importance-weighted" estimators in the overparameterized regime Kuo-Wei Lai Vidya Muthukumar 90 0 0 10 May 2024
Fast Computation of Leave-One-Out Cross-Validation for $k$ -NN Regression Motonobu Kanagawa 384 0 0 08 May 2024
Causally Inspired Regularization Enables Domain General Representations Olawale Salaudeen Oluwasanmi Koyejo OOD CML 63 2 0 25 Apr 2024
Transfer Learning Beyond Bounded Density Ratios Alkis Kalavasis Ilias Zadik Manolis Zampetakis 94 5 0 18 Mar 2024
On the design-dependent suboptimality of the Lasso Reese Pathak Cong Ma 72 5 0 01 Feb 2024
Transfer Learning for Functional Mean Estimation: Phase Transition and Adaptive Algorithms T. T. Cai Dongwoo Kim Hongming Pu 94 9 0 22 Jan 2024
Mitigating Covariate Shift in Misspecified Regression with Applications to Reinforcement Learning Philip Amortila Tongyi Cao Akshay Krishnamurthy OffRL OOD 71 3 0 22 Jan 2024
Transfer Learning under Covariate Shift: Local $k$ -Nearest Neighbours Regression with Heavy-Tailed Design Petr Zamolodtchikov Hanyuan Hang OOD 35 0 0 21 Jan 2024
Nearest Neighbor Sampling for Covariate Shift Adaptation Franccois Portier Lionel Truquet Ikko Yamane OffRL 39 1 0 15 Dec 2023
Invariance assumptions for class distribution estimation Dirk Tasche OOD 68 4 0 28 Nov 2023
Model-free Test Time Adaptation for Out-Of-Distribution Detection Yi-Fan Zhang Xue Wang Tian Zhou Kun Yuan Zhang Zhang Liang Wang Rong Jin Tien-Ping Tan TTA OODD 80 4 0 28 Nov 2023
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift Xingdong Feng Xin He Caixing Wang Chao Wang Jingnan Zhang 69 7 0 12 Oct 2023
Covariate shift in nonparametric regression with Markovian design Lukas Trottner 54 0 0 17 Jul 2023
Best-Effort Adaptation Pranjal Awasthi Corinna Cortes M. Mohri 86 8 0 10 May 2023
Classification Tree Pruning Under Covariate Shift Nicholas Galbraith Samory Kpotufe 78 1 0 07 May 2023
Limits of Model Selection under Transfer Learning Steve Hanneke Samory Kpotufe Yasaman Mahdaviyeh 116 6 0 29 Apr 2023
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation Yi-Fan Zhang Xue Wang Kexin Jin Kun Yuan Zhang Zhang Liang Wang Rong Jin Tien-Ping Tan TTA OOD 93 44 0 25 Apr 2023
Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints Reese Pathak Martin J. Wainwright Lin Xiao 58 5 0 22 Mar 2023
When is Importance Weighting Correction Needed for Covariate Shift Adaptation? Davit Gogolashvili Matteo Zecchin Motonobu Kanagawa Marios Kountouris Maurizio Filippone 65 7 0 07 Mar 2023
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift Kaizheng Wang 66 12 0 20 Feb 2023
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation Yu Zhang Zhenyu Zhang Peng Zhao Masashi Sugiyama OOD 83 13 0 06 Feb 2023
Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations Olawale Salaudeen Oluwasanmi Koyejo 74 3 0 21 Dec 2022
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria Tengyuan Liang 74 1 0 05 Dec 2022
Transfer Learning for Contextual Multi-armed Bandits Changxiao Cai T. Tony Cai Hongzhe Li 127 19 0 22 Nov 2022
The out-of-sample prediction error of the square-root-LASSO and related estimators J. M. Olea Cynthia Rush Amilcar Velez J. Wiesel OOD 90 6 0 14 Nov 2022
Importance Weighting Correction of Regularized Least-Squares for Covariate and Target Shifts Davit Gogolashvili OOD 54 1 0 18 Oct 2022
Automatically Score Tissue Images Like a Pathologist by Transfer Learning Iris Yan MedIm 22 1 0 09 Sep 2022
Domain-Specific Risk Minimization for Out-of-Distribution Generalization Yi-Fan Zhang Jindong Wang Jian Liang Zhang Zhang Baosheng Yu Liangdao Wang Dacheng Tao Xingxu Xie OOD 119 17 0 18 Aug 2022
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift Jingfeng Wu Difan Zou Vladimir Braverman Quanquan Gu Sham Kakade 65 17 0 03 Aug 2022
Breaking Correlation Shift via Conditional Invariant Regularizer Mingyang Yi Ruoyu Wang Jiacheng Sun Zhenguo Li Zhi-Ming Ma OODD 91 5 0 14 Jul 2022
A Correlation-Ratio Transfer Learning and Variational Stein's Paradox Lu Lin Weiyu Li 54 3 0 10 Jun 2022
On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis Xuetong Wu Biwei Huang J. Manton U. Aickelin Jingge Zhu CML 57 2 0 10 May 2022
Optimally tackling covariate shift in RKHS-based nonparametric regression Cong Ma Reese Pathak Martin J. Wainwright 61 45 0 06 May 2022
Connecting sufficient conditions for domain adaptation: source-guided uncertainty, relaxed divergences and discrepancy localization Sofien Dhouib S. Maghsudi 83 2 0 09 Mar 2022
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality Xuhui Zhang Jose H. Blanchet Soumyadip Ghosh M. Squillante 65 9 0 23 Feb 2022
Adaptive and Robust Multi-Task Learning Yaqi Duan Kaizheng Wang 130 27 0 10 Feb 2022
A new similarity measure for covariate shift with applications to nonparametric regression Reese Pathak Cong Ma Martin J. Wainwright 96 32 0 06 Feb 2022
On the Limitations of General Purpose Domain Generalisation Methods Henry Gouk Ondrej Bohdal Da Li Timothy M. Hospedales 78 11 0 01 Feb 2022