% Key papers for Surrogate losses and robust solvers (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2019_deep_14028,
  title = {{Deep Metric Learning to Rank}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_mean_13363,
  title = {{Mean-Variance Loss for Deep Age Estimation From a Face}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Pan_Mean-Variance_Loss_for_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_a_13799,
  title = {{A Variational Pan-Sharpening With Local Gradient Constraints}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{iclr2018_learning_28491,
  title = {{Learning Sparse Neural Networks through L\_0 Regularization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/222},
}

@inproceedings{cvpr2016_fits_11557,
  title = {{Fits Like a Glove: Rapid and Reliable Hand Shape Personalization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2022_herosnet_18992,
  title = {{HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2018_scalable_13561,
  title = {{Scalable and Effective Deep CCA via Soft Decorrelation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Chang_Scalable_and_Effective_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_a_13778,
  title = {{A Local Block Coordinate Descent Algorithm for the CSC Model}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_baseline_12860,
  title = {{Baseline Desensitizing in Translation Averaging}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zhuang_Baseline_Desensitizing_in_CVPR_2018_paper.html},
}

@inproceedings{neurips2017_multiscale_56497,
  title = {{Multiscale Quantization for Fast Similarity Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9348},
}

@inproceedings{cvpr2022_recall_19685,
  title = {{Recall@k Surrogate Loss With Large Batches and Similarity Mixup}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{icml2019_learning_37491,
  title = {{Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3980},
}

@inproceedings{icml2017_developing_36147,
  title = {{Developing Bug-Free Machine Learning Systems With Formal Mathematics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/849},
}

@inproceedings{aaai2020_transparent_102240,
  title = {{Transparent Classification with Multilayer Logical Perceptrons and Random Binarization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6102},
}

@inproceedings{neurips2021_stochastic_63510,
  title = {{Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27284},
}

@inproceedings{cvpr2024_lp_23902,
  title = {{LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30334},
}

@inproceedings{aaai2023_fedmdfg_3684,
  title = {{FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26122},
}

@inproceedings{icml2016_learning_35889,
  title = {{Learning from Multiway Data: Simple and Efficient Tensor Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/yu16.html},
}

@inproceedings{iclr2018_unbiased_28671,
  title = {{Unbiased Online Recurrent Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/184},
}

@inproceedings{cvpr2020_minimizing_15892,
  title = {{Minimizing Discrete Total Curvature for Image Processing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2024_qn_24549,
  title = {{QN-Mixer: A Quasi-Newton MLP-Mixer Model for Sparse-View CT Reconstruction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31405},
}

@inproceedings{neurips2024_unified_73105,
  title = {{Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94324},
}

@inproceedings{cvpr2025_balanced_25566,
  title = {{Balanced Rate-Distortion Optimization in Learned Image Compression}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35034},
}

@inproceedings{neurips2024_langevin_70343,
  title = {{Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96754},
}

@inproceedings{neurips2024_certified_73352,
  title = {{Certified Machine Unlearning via Noisy Stochastic Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94094},
}

@inproceedings{icml2024_interpreting_45352,
  title = {{Interpreting and Improving Diffusion Models from an Optimization Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33099},
}

@inproceedings{iclr2024_grande_34617,
  title = {{GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18457},
}

@inproceedings{iclr2024_efficient_34338,
  title = {{Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18737},
}

@inproceedings{icml2024_plug_44837,
  title = {{Plug-and-Play image restoration with Stochastic deNOising REgularization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33615},
}

@inproceedings{neurips2024_fast_70129,
  title = {{Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96949},
}

@inproceedings{neurips2024_learning_74337,
  title = {{Learning from Uncertain Data: From Possible Worlds to Possible Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93223},
}

@inproceedings{aaai2025_approximating_8137,
  title = {{Approximating Metric Magnitude of Point Sets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33687},
}

@inproceedings{iclr2024_unconstrained_34361,
  title = {{Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18714},
}

@inproceedings{icml2024_learning_43936,
  title = {{Learning Pseudo-Contractive Denoisers for Inverse Problems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34516},
}

@inproceedings{icml2024_careful_44034,
  title = {{Careful with that Scalpel: Improving Gradient Surgery with an EMA}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34418},
}

@inproceedings{icml2024_mitigating_45590,
  title = {{Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32862},
}

@inproceedings{icml2024_lookbehind_45661,
  title = {{Lookbehind-SAM: k steps back, 1 step forward}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32791},
}

@inproceedings{icml2025_leveraging_45846,
  title = {{Leveraging Per-Instance Privacy for Machine Unlearning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46697},
}

@inproceedings{icml2025_parq_46278,
  title = {{PARQ: Piecewise-Affine Regularized Quantization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46282},
}