Covariate Shift

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Covariate shift occurs when source and deployment inputs have different distributions, even though the rule linking inputs to labels is assumed to stay the same. Common approaches reweight labeled source examples using estimated density ratios, match source and target feature distributions, or learn representations that transfer better; clipping and regularization can limit unstable weights. Researchers also use conformal prediction, calibration, and risk-estimation methods to assess coverage and reliability without many labeled target examples, including in image, medical, and geographic transfer settings. A central tension is that reweighting needs adequate source–target overlap and can become noisy when ratios are large, while real shifts may also change the label relationship and invalidate covariate-only assumptions.

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51 papers8 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

Shift-aware score transport for privacy auditing without retraining
Oct 22, 2026Yaohong Yang, Gauri Pradhan, Qi Chen +2Privacy Auditing Covariate Shift
ELLIS Institute Finland · Department of Computer Science, Aalto University, Finland · Department of Computer Science, University of Helsinki, Finland +1
When Does Training on Synthetic Data Provably Work?
Oct 20, 2026Leroy Odunlami, Tobias Riedlinger, Hanno GottschalkSynthetic-to-Real Domain Adaptation Covariate Shift
Institute of Mathematics, Technische Universität Berlin, Berlin, Germany
Diagnosing Low-Confidence Patient Profiles via Localized Harmful Covariate Shift Detection
Oct 13, 2026Olivier Lefebvre, Hakima Laribi, Dan Poenaru +1Distribution Shift Detection Clinical Prediction
Department of Computer Science, Université de Sherbrooke, Sherbrooke, Canada · Department of Pediatric Surgery, Montreal Children's Hospital, Montreal, Canada · Centre for Outcomes Research and Evaluation +1
Reliable Risk Estimation with Kernel Mean Matching under Dependent Sampling
Oct 13, 2026Alexey Zaytsev, Diana Koldasbayeva, Egor SerovKernel Methods Statistical Learning Theory
Applied AI Institute
Backward Conformal Prediction under Covariate Shift
Oct 12, 2026Amin Meghrazi, Yuanyuan LiConformal Prediction Weighted Conformal Prediction
The Ohio State University · Munich RE
Latent-Space Importance Weighting under Covariate Shift
Oct 11, 2026Yuling Jiao, Lican Kang, Yang Xiang +2Covariate Shift Transfer Learning
School of Artificial Intelligence, and Hubei Key Laboratory of Computational Science, Wuhan University, Wuhan, 430072, China · Institute for Math and AI, Wuhan University, Wuhan, 430072, China · Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China, and Algorithms of Machine Learning and Autonomous Driving Research Lab, HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Shenzhen, China +2
Rethinking Data Augmentation under Covariate Shift: Invariant-Guided Diffusion and Prototype Reweighting
Oct 1, 2026Hongyu Cao, Xinyuan Wang, Arun Vignesh Malarkkan +3Synthetic Data Augmentation Diffusion Model Guidance
School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281 USA
How Much Can Reliability Drift Under a Fixed Confidence Distribution?
Sep 30, 2026Wenhao Liang, Lin Yue, Wei Emma Zhang +3Distribution Shift Robustness Probability Calibration
Adelaide University
Sharp training-conditional coverage for conformal prediction under covariate shift
Sep 27, 2026Mehrdad PournaderiWeighted Conformal Prediction Set Prediction
Mofid Securities
Is Online Interaction Necessary for Recovery? A Minimalist Approach to Robust Planning via Perturbation
Sep 27, 2026Bumgeun Park, Donghwan LeeRobot Imitation Learning Behavior Cloning
Korea Advanced Institute of Science and Technology (KAIST)
Policy-Calibrated DAgger: Offline Calibrated Noise Injection for Imitation Learning
Sep 24, 2026Jenny Wang, George KantorRobot Imitation Learning Covariate Shift
Carnegie Mellon University, Pittsburgh PA, USA
Conformalized Quantile Regression and Minimax Limits of Fixed-Score Calibration under Known Covariate Shift
Sep 21, 2026Rustam Isaev, Anton Conrad, Denis Belomestny +2Conformal Prediction Covariate Shift
Faculty of Computer Science, HSE University, Moscow, Russia · Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia · Laboratoire de Recherche d’EPITA, Le Kremlin-Bicêtre, France +2
Cross-Material Support Transfer for Core-Loss Prediction Under Waveform Covariate Shift
Sep 15, 2026Cong Yao, Chunye GongMaterials Property Prediction Transfer Learning
School of Computer Science and Technology, Changsha University of Science and Technology, Changsha 410076, China · College of Computing, National University of Defense Technology, Changsha 410073, China · National Supercomputer Center in Tianjin, Tianjin 300457, China +1
General Quantification of Covariate and Concept Shifts
Sep 10, 2026Hongbo Chen, Li Charlie XiaDistribution Shift Concept Drift
Department of Statistics and Financial Mathematics, School of Mathematics, South China University of Technology, Guangzhou, China.
Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction
Sep 10, 2026Ann-Kristin Malz, Gregory Ashton, Nicolo ColomboWeighted Conformal Prediction Gravitational-Wave Astronomy
Department of Physics, Royal Holloway, University of London · School of Mathematical Sciences, University of Southampton · Department of Computer Science, Royal Holloway University of London
Conformal Calibration Transfer
Sep 9, 2026Achref DoulaWeighted Conformal Prediction Conformal Prediction
Technical University of Darmstadt, Darmstadt, Germany · Tongji University, Shanghai, China.
CS-WCP: Robust Conformal Sets for LLM-Judge Traffic Shifts with Uncertain Group Proportions
Aug 23, 2026Ibne Farabi Shihab, Fariya AfrinConformal Prediction Weighted Conformal Prediction
Department of Computer Science, Iowa State University · Department of Computer Science, Kalinga Institute of Industrial Technology
Separating Covariate Shift from Mechanism Change with Two Discriminators: CJSD, a Conditional Discrepancy with an Exact Covariate-Concept Decomposition
Aug 20, 2026Kentaro OdaDistribution Shift Detection Covariate Shift
Center for Management of Information Technologies, Kagoshima University
Inferential Evaluation of Surrogate-Derived Models under Covariate Shift
Aug 16, 2026Longtian Shi, Molei Liu, Doudou ZhouDistribution Shift Robustness Covariate Shift
Department of Statistics and Data Science, National University of Singapore · Department of Biostatistics, Peking University Health Science Center, Peking University, Beijing, China · Beijing International Center for Mathematical Research, Peking University, Beijing, China
Certify or Refuse: A Cross-Model Map for Selective Risk Control with Coverage Floors under Covariate Shift
Aug 11, 2026Jiamiao Liu, Dewen Qiao, Yu Zhang +1Selective Prediction Covariate Shift
Department of Information, Xinqiao Hospital Army Medical University (Third Military Medical University) Chongqing 400037, China
Nonparametric Goodness-of-fit Testing under Covariate Shift
Aug 5, 2026Zhen Hou, Dong XiaKernel Ridge Regression Covariate Shift
Department of Mathematics Hong Kong University of Science and Technology
Augmented Inverse Hybrid Weighting: Robust Inference under Deterministic and Random Distribution Shifts
Aug 1, 2026Ying Jin, Ying Jin, Dominik RothenhäuslerInverse Probability Weighting Distribution Shift Robustness
Beyond Random Partitioning: Unsupervised Spatio-Temporal Stratification for Cohort Balancing in Longitudinal Medical Imaging
Jul 29, 2026Qinghui Liu, Jon André Ottesen, Atle Bjørnerud +1Longitudinal Medical Image Analysis Covariate Shift
Department of Physics and Computational Radiology, Oslo University Hospital, Norway
PIcsC: Partitioning-Induced Covariate Shift Correction
Jul 28, 2026Behraj Khan, Behroz Mirza, Syed Ahmad Chan Bukhari +1Non-IID Federated Learning Covariate Shift
School of Mathematics and Computer Science, Institute of Business Administration Karachi, Pakistan. · Department of Computer Science, Habib University, Karachi, Pakistan. · Division of Computer Science, Mathematics and Science, St. John’s University, USA.
Adaptive deep nonparametric regression from dependent data under covariate shift
Jul 22, 2026William Kengne, Ehud Mossa OckegnaQuantile Regression Covariate Shift
Université Jean Monnet, ICJ UMR5208, CNRS, Ecole Centrale de Lyon, INSA Lyon, Universite Claude Bernard Lyon 1, 42000 Saint-Étienne, France
Convergence Analysis of Nyström Subsampling in Covariate Shift Adaptation for Misspecified case
Jun 20, 2026Hanna Myleiko, Sergei Solodky, Vasyl SemenovUnsupervised Domain Adaptation Domain Adaptation
Institute of Mathematics NAS of Ukraine, 3 Tereschenkivska st., Kyiv, Ukraine. · Institute of Mathematics NAS of Ukraine, 3 Tereschenkivska st., Kyiv, Ukraine · University of Giessen, Department of Mathematics, Giessen, Germany. +1
Conformal Candidate Certification for Offline Model-Based Optimization
Jun 13, 2026Seungjin ChoiWeighted Conformal Prediction Distribution Shift
CROID Research and aSSIST University, Seoul, Korea.
Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias
Jun 12, 2026Annie Ulichney, Amanda CostonDouble ML Distribution Shift Robustness
Department of Statistics, University of California, Berkeley
Realistic noise synthesis reduces bias and improves tissue microstructure estimation with supervised machine learning
Jun 1, 2026Bradley G. Karat, Maëliss Jallais, Ali R. Khan +3Parameter Estimation Distribution Shift
Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Canada · Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, New York, USA · Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom +3
From Local Geometry to Global Pseudo Labeling for Robust Positive Unlabeled Learning under Covariate Shift
May 29, 2026Firas Gabetni, Alexandre Rocchi Henry, Nacim Belkhir +2Distribution Shift Robustness Covariate Shift
U2IS, ENSTA · Institut Polytechnique de Paris · AMIAD, Pôle Recherche, Palaiseau

Oct 22, 2026J/K move · Enter open · S save

Shift-aware score transport for privacy auditing without retraining

Yaohong Yang, Gauri Pradhan, Qi Chen, Samuel Kaski+1

ELLIS Institute Finland · Department of Computer Science, Aalto University, Finland · Department of Computer Science, University of Helsinki, Finland+1

Privacy Auditing Covariate Shift Membership Inference Attacks

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Privacy auditing empirically assesses privacy leakage by using membership inference attacks to establish lower bounds on privacy loss. We consider an observational auditing setting in which the auditor cannot insert canaries, control data inclusion, or retrain the target model, and must instead rely on fixed sets of known members and non-members. This setting is relevant for large deployed models or when retraining is restricted by computational or access constraints. In this case, non-members available for auditing may differ in distribution from the training data, causing membership-inference scores to be skewed due to the distribution shift. We address this problem by estimating the counterfactual in-distribution non-member score distribution using the available out-of-distribution (OOD) non-members. Our proposed method learns the relationship between data representations and membership-inference scores from OOD non-members and transports it to the target covariate distribution. Because this transport may become unreliable under extrapolation or imperfect conditional invariance, we further introduce a conservative correction calibrated directly to the nominal transported privacy level. We construct controlled calibration tasks from the available non-member data to estimate how representation-space displacement inflates the audit, and use this estimate to correct the transport-induced audit error. Across multiple datasets with distribution shifts, our method yields substantially more stable privacy estimates while retaining tighter lower bounds than baselines.