% Key papers for Random feature approximation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_orthogonal_55928,
  title = {{Orthogonal Random Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7415},
}

@inproceedings{icml2017_random_36356,
  title = {{Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/800},
}

@inproceedings{neurips2016_learning_55820,
  title = {{Learning Kernels with Random Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6979},
}

@inproceedings{neurips2017_gaussian_56336,
  title = {{Gaussian Quadrature for Kernel Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9382},
}

@inproceedings{neurips2018_quadrature_57541,
  title = {{Quadrature-based features for kernel approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11872},
}

@inproceedings{aaai2018_on_102430,
  title = {{On Data-Dependent Random Features for Improved Generalization in Supervised Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11697},
}

@inproceedings{aaai2020_random_102058,
  title = {{Random Fourier Features via Fast Surrogate Leverage Weighted Sampling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5920},
}

@inproceedings{aaai2018_deep_102483,
  title = {{Deep Semi-Random Features for Nonlinear Function Approximation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11750},
}

@inproceedings{aaai2019_learning_101623,
  title = {{Learning Adaptive Random Features}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4329},
}

@inproceedings{cvpr2016_random_11786,
  title = {{Random Features for Sparse Signal Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2020_learning_60243,
  title = {{Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17351},
}

@inproceedings{icml2019_towards_37812,
  title = {{Towards a Unified Analysis of Random Fourier Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4235},
}

@inproceedings{aaai2019_random_101500,
  title = {{Random Feature Maps for the Itemset Kernel}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4188},
}

@inproceedings{aaai2017_random_104448,
  title = {{Random Features for Shift-Invariant Kernels with Moment Matching}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10825},
}

@inproceedings{icml2021_quantization_39842,
  title = {{Quantization Algorithms for Random Fourier Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8733},
}

@inproceedings{neurips2022_chefs_66310,
  title = {{Chefs' Random Tables: Non-Trigonometric Random Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54800},
}

@inproceedings{neurips2023_tanimoto_67854,
  title = {{Tanimoto Random Features for Scalable Molecular Machine Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71908},
}

@inproceedings{aaai2022_trf_2807,
  title = {{TRF: Learning Kernels with Tuned Random Features}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08286-trf-learning-kernels-with-tuned-random-features/},
}

@inproceedings{icml2023_simplex_42998,
  title = {{Simplex Random Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24847},
}

@inproceedings{neurips2018_streaming_57659,
  title = {{Streaming Kernel PCA with \$tildeO(sqrtn)\$ Random Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11704},
}

@inproceedings{icml2024_optimal_44109,
  title = {{Optimal Kernel Quantile Learning with Random Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34343},
}

@inproceedings{neurips2024_efficiently_71002,
  title = {{Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96204},
}

@inproceedings{iclr2025_variance_83452,
  title = {{Variance-Reducing Couplings for Random Features}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28364},
}

@inproceedings{iclr2026_scalable_87793,
  title = {{Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=fWhRslwYri},
}

@inproceedings{iclr2026_probabilistic_88489,
  title = {{Probabilistic Kernel Function for Fast Angle Testing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=nCsF3Bsn2n},
}

@inproceedings{neurips2026_manifold_93536,
  title = {{Manifold Random Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152522},
}

@inproceedings{icml2024_quasi_45026,
  title = {{Quasi-Monte Carlo Features for Kernel Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33426},
}

@inproceedings{icml2026_scalable_53599,
  title = {{Scalable and Stable Estimation of Amari \$alpha\$-Divergence using Random Fourier Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=gyxhoU9rbm},
}

@inproceedings{neurips2026_ldd_95103,
  title = {{LDD-RFM: Learnable Domain Decomposition for Random Feature Models via Variable Projection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152971},
}