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

@inproceedings{neurips2016_mutual_55887,
  title = {{Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6975},
}

@inproceedings{neurips2016_sub_56024,
  title = {{Sub-sampled Newton Methods with Non-uniform Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7191},
}

@inproceedings{cvpr2017_revisiting_12585,
  title = {{Revisiting the Variable Projection Method for Separable Nonlinear Least Squares Problems}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2017_zap_56780,
  title = {{Zap Q-Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9011},
}

@inproceedings{cvpr2017_consensus_12122,
  title = {{Consensus Maximization With Linear Matrix Inequality Constraints}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{aaai2016_scalable_105094,
  title = {{Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10266},
}

@inproceedings{aaai2017_a_101070,
  title = {{A Unified Convex Surrogate for the Schatten-p Norm}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10646},
}

@inproceedings{icml2016_fast_35842,
  title = {{Fast methods for estimating the Numerical rank of large matrices}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/ubaru16.html},
}

@inproceedings{neurips2019_variance_59174,
  title = {{Variance Reduction for Matrix Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13237},
}

@inproceedings{neurips2016_cma_55612,
  title = {{CMA-ES with Optimal Covariance Update and Storage Complexity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7277},
}

@inproceedings{neurips2017_unbiased_56743,
  title = {{Unbiased estimates for linear regression via volume sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9093},
}

@inproceedings{neurips2017_fixed_56324,
  title = {{Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8915},
}

@inproceedings{cvpr2019_perturbation_14638,
  title = {{Perturbation Analysis of the 8-Point Algorithm: A Case Study for Wide FoV Cameras}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{neurips2018_spectral_57641,
  title = {{Spectral Filtering for General Linear Dynamical Systems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11456},
}

@inproceedings{aaai2019_complex_101586,
  title = {{Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4280},
}

@inproceedings{icml2017_on_36313,
  title = {{On Approximation Guarantees for Greedy Low Rank Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/877},
}

@inproceedings{icml2017_toward_36433,
  title = {{Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/473},
}

@inproceedings{icml2016_towards_36013,
  title = {{Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/gui16.html},
}

@inproceedings{cvpr2018_fast_13105,
  title = {{Fast and Robust Estimation for Unit-Norm Constrained Linear Fitting Problems}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Ikami_Fast_and_Robust_CVPR_2018_paper.html},
}

@inproceedings{icml2016_gaussian_35849,
  title = {{Gaussian quadrature for matrix inverse forms with applications}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/lig16.html},
}

@inproceedings{neurips2024_adaptive_72643,
  title = {{Adaptive Sampling for Efficient Softmax Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94739},
}

@inproceedings{neurips2024_nearly_70391,
  title = {{Nearly Optimal Approximation of Matrix Functions by the Lanczos Method}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96711},
}

@inproceedings{icml2025_guarantees_46749,
  title = {{Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45824},
}

@inproceedings{neurips2024_matrix_71880,
  title = {{Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95423},
}

@inproceedings{neurips2024_on_72923,
  title = {{On the Complexity of Identification in Linear Structural Causal Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94488},
}

@inproceedings{neurips2025_polar_78875,
  title = {{PoLAR: Polar-Decomposed Low-Rank Adapter Representation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=jDxFD45kkc},
}

@inproceedings{iclr2025_singular_81479,
  title = {{Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30296},
}

@inproceedings{aaai2024_the_7545,
  title = {{The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30014},
}

@inproceedings{iclr2024_optimal_34443,
  title = {{Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18632},
}

@inproceedings{icml2024_turnstile_45224,
  title = {{Turnstile \$ell\_p\$ leverage score sampling with applications}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33228},
}

@inproceedings{icml2024_reweighted_45483,
  title = {{Reweighted Solutions for Weighted Low Rank Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32968},
}

@inproceedings{icml2025_gl_47444,
  title = {{GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45149},
}

@inproceedings{icml2025_fluctuations_49062,
  title = {{Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43562},
}

@inproceedings{icml2026_an_54712,
  title = {{An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=rlvnG8oKmN},
}

@inproceedings{icml2026_even_54994,
  title = {{Even Faster Kernel Matrix Linear Algebra via Density Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ueNIrBXz7R},
}

@inproceedings{neurips2024_coherence_71089,
  title = {{Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96125},
}

@inproceedings{neurips2024_invariant_72572,
  title = {{Invariant subspaces and PCA in nearly matrix multiplication time}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94800},
}

@inproceedings{neurips2024_fasme_74406,
  title = {{FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93163},
}

@inproceedings{neurips2024_entrywise_74655,
  title = {{Entrywise error bounds for low-rank approximations of kernel matrices}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/92940},
}

@inproceedings{neurips2025_spectral_74883,
  title = {{Spectral Estimation with Free Decompression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2CeGVUpOd7},
}