% Key papers for Kernel regression under shift (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2016_object_11735,
  title = {{Object Tracking via Dual Linear Structured SVM and Explicit Feature Map}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2017_product_12553,
  title = {{Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{aaai2018_kernel_102443,
  title = {{Kernel Cross-Correlator}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11710},
}

@inproceedings{icml2016_persistence_35947,
  title = {{Persistence weighted Gaussian kernel for topological data analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/kusano16.html},
}

@inproceedings{cvpr2018_high_13189,
  title = {{High-Speed Tracking With Multi-Kernel Correlation Filters}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Tang_High-Speed_Tracking_With_CVPR_2018_paper.html},
}

@inproceedings{aaai2019_fast_101596,
  title = {{Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4291},
}

@inproceedings{icml2016_nonparametric_35922,
  title = {{Nonparametric Canonical Correlation Analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/michaeli16.html},
}

@inproceedings{cvpr2017_incremental_12354,
  title = {{Incremental Kernel Null Space Discriminant Analysis for Novelty Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2017_a_12007,
  title = {{A General Framework for Curve and Surface Comparison and Registration With Oriented Varifolds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2018_persistence_57506,
  title = {{Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11949},
}

@inproceedings{neurips2020_minimax_60321,
  title = {{Minimax Estimation of Conditional Moment Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18701},
}

@inproceedings{neurips2020_calibrated_59502,
  title = {{Calibrated Reliable Regression using Maximum Mean Discrepancy}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18260},
}

@inproceedings{neurips2017_group_56355,
  title = {{Group Sparse Additive Machine}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8817},
}

@inproceedings{neurips2022_efficient_65671,
  title = {{Efficient Dataset Distillation using Random Feature Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53813},
}

@inproceedings{neurips2022_learning_65037,
  title = {{Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53255},
}

@inproceedings{icml2019_monk_37527,
  title = {{MONK Outlier-Robust Mean Embedding Estimation by Median-of-Means}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3874},
}

@inproceedings{aaai2016_extending_105129,
  title = {{Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10301},
}

@inproceedings{aaai2023_practical_4396,
  title = {{Practical Markov Boundary Learning without Strong Assumptions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26236},
}

@inproceedings{neurips2019_solving_58994,
  title = {{Solving Interpretable Kernel Dimensionality Reduction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13868},
}

@inproceedings{aaai2016_discriminative_105051,
  title = {{Discriminative Vanishing Component Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10223},
}

@inproceedings{aaai2025_error_9010,
  title = {{Error Bounds for Gaussian Process Regression Under Bounded Support Noise with Applications to Safety Certification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34220},
}

@inproceedings{icml2024_on_45270,
  title = {{On Hypothesis Transfer Learning of Functional Linear Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33182},
}

@inproceedings{aaai2025_bridging_8314,
  title = {{Bridging the Gap Between Hyperdimensional Computing and Kernel Methods via the Nyström Method}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34442},
}

@inproceedings{iclr2024_smooth_34635,
  title = {{Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18439},
}

@inproceedings{neurips2024_towards_71234,
  title = {{Towards a Scalable Reference-Free Evaluation of Generative Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96008},
}

@inproceedings{neurips2024_sample_72150,
  title = {{Sample-efficient Bayesian Optimisation Using Known Invariances}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95186},
}

@inproceedings{aaai2024_multi_6712,
  title = {{Multi-View Randomized Kernel Classification via Nonconvex Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29064},
}

@inproceedings{icml2024_smoothness_45652,
  title = {{Smoothness Adaptive Hypothesis Transfer Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32800},
}

@inproceedings{iclr2024_spectrally_34341,
  title = {{Spectrally Transformed Kernel Regression}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18734},
}

@inproceedings{icml2024_on_43674,
  title = {{On the Consistency of Kernel Methods with Dependent Observations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34778},
}

@inproceedings{icml2024_learning_43963,
  title = {{Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34489},
}

@inproceedings{icml2024_position_45694,
  title = {{Position: \$C^*\$-Algebraic Machine Learning \$-\$ Moving in a New Direction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32758},
}

@inproceedings{icml2025_towards_46588,
  title = {{Towards an Explainable Comparison and Alignment of Feature Embeddings}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45981},
}

@inproceedings{icml2025_peaks_46711,
  title = {{PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45861},
}

@inproceedings{icml2025_laplace_46791,
  title = {{Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45784},
}

@inproceedings{icml2026_conditional_50070,
  title = {{Conditional KRR: Injecting Unpenalized Features into Kernel Methods with Applications to Kernel Thresholding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=8mGDNFoJOD},
}

@inproceedings{icml2026_asymmetric_53215,
  title = {{Asymmetric conformal prediction with penalized kernel sum-of-squares}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=dNaRpdbnOG},
}

@inproceedings{icml2026_pca_54827,
  title = {{PCA of Probability Measures: Sparse and Dense Sampling Regimes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=t4SltdwuLF},
}

@inproceedings{icml2026_any_55184,
  title = {{Any-dimensional invariant universality}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=wRVTDcEMv8},
}

@inproceedings{neurips2024_a_71705,
  title = {{A Kernel Perspective on Distillation-based Collaborative Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95580},
}