% Key papers for Multi-fidelity hyperparameter optimization (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2018_bohb_36535,
  title = {{BOHB: Robust and Efficient Hyperparameter Optimization at Scale}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2387},
}

@inproceedings{iclr2017_learning_28292,
  title = {{Learning Curve Prediction with Bayesian Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=S11KBYclx},
}

@inproceedings{aaai2017_efficient_101071,
  title = {{Efficient Hyperparameter Optimization for Deep Learning Algorithms Using Deterministic RBF Surrogates}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10647},
}

@inproceedings{neurips2018_probabilistic_57530,
  title = {{Probabilistic Matrix Factorization for Automated Machine Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11337},
}

@inproceedings{icml2018_autoprognosis_36530,
  title = {{AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2050},
}

@inproceedings{aaai2021_warm_1625,
  title = {{Warm Starting CMA-ES for Hyperparameter Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09188-warm-starting-cma-es-for-hyperparameter-optimization/},
}

@inproceedings{aaai2020_efficient_102048,
  title = {{Efficient Automatic CASH via Rising Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5910},
}

@inproceedings{aaai2021_mfes_956,
  title = {{MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08491-mfes-hb-efficient-hyperband-with-multi-fidelity-quality-measurements/},
}

@inproceedings{icml2018_structured_37021,
  title = {{Structured Variationally Auto-encoded Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2328},
}

@inproceedings{neurips2019_safe_58937,
  title = {{Safe Exploration for Interactive Machine Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13473},
}

@inproceedings{neurips2020_model_60334,
  title = {{Model Inversion Networks for Model-Based Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17613},
}

@inproceedings{neurips2021_explaining_63011,
  title = {{Explaining Hyperparameter Optimization via Partial Dependence Plots}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27169},
}

@inproceedings{neurips2022_modeling_64105,
  title = {{Modeling the Machine Learning Multiverse}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54265},
}

@inproceedings{aaai2024_pg_6891,
  title = {{PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29018},
}

@inproceedings{cvpr2024_efficient_23330,
  title = {{Efficient Hyperparameter Optimization with Adaptive Fidelity Identification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31652},
}

@inproceedings{aaai2021_high_716,
  title = {{High Dimensional Level Set Estimation with Bayesian Neural Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/12095-high-dimensional-level-set-estimation-with-bayesian-neural-network/},
}

@inproceedings{iclr2021_few_30455,
  title = {{Few-Shot Bayesian Optimization with Deep Kernel Surrogates}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3163},
}

@inproceedings{aaai2019_deep_100587,
  title = {{Deep Bayesian Optimization on Attributed Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3938},
}

@inproceedings{iclr2021_autolrs_30326,
  title = {{AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3054},
}

@inproceedings{icml2022_nomu_40865,
  title = {{NOMU: Neural Optimization-based Model Uncertainty}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16225},
}

@inproceedings{icml2024_probability_44654,
  title = {{Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33798},
}

@inproceedings{neurips2024_generative_70353,
  title = {{Generative Adversarial Model-Based Optimization via Source Critic Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96744},
}

@inproceedings{neurips2024_model_73665,
  title = {{Model Fusion through Bayesian Optimization in Language Model Fine-Tuning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93827},
}

@inproceedings{icml2025_optimization_46906,
  title = {{Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45674},
}

@inproceedings{icml2025_multi_47959,
  title = {{Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44646},
}

@inproceedings{neurips2024_uq_73568,
  title = {{UQ-Guided Hyperparameter Optimization for Iterative Learners}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93913},
}

@inproceedings{neurips2025_data_76588,
  title = {{Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Kvsa8ZXd0W},
}

@inproceedings{iclr2026_discount_88382,
  title = {{Discount Model Search for Quality Diversity Optimization in High-Dimensional Measure Spaces}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=m6Hv0yZO3n},
}

@inproceedings{neurips2026_post_95373,
  title = {{Post-ADC Inference: Valid Inference After Active Data Collection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151721},
}

@inproceedings{aaai2026_lamda_108678,
  title = {{LAMDA: Two-Phase HPO via Learning Prior from Low-Fidelity Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/41030},
}

@inproceedings{cvpr2026_dabo_98845,
  title = {{DABO: Difficulty-Aware Bayesian Optimization with Diffusion-Learned Priors}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Li_DABO_Difficulty-Aware_Bayesian_Optimization_with_Diffusion-Learned_Priors_CVPR_2026_paper.html},
}