@inproceedings{langley00,
 author    = {P. Langley},
 title     = {Crafting Papers on Machine Learning},
 year      = {2000},
 pages     = {1207--1216},
 editor    = {Pat Langley},
 booktitle     = {Proceedings of the 17th International Conference
              on Machine Learning (ICML 2000)},
 address   = {Stanford, CA},
 publisher = {Morgan Kaufmann}
}

@TechReport{mitchell80,
  author = 	 "T. M. Mitchell",
  title = 	 "The Need for Biases in Learning Generalizations",
  institution =  "Computer Science Department, Rutgers University",
  year = 	 "1980",
  address =	 "New Brunswick, MA",
}

@phdthesis{kearns89,
  author = {M. J. Kearns},
  title =  {Computational Complexity of Machine Learning},
  school = {Department of Computer Science, Harvard University},
  year =   {1989}
}

@Book{MachineLearningI,
  editor = 	 "R. S. Michalski and J. G. Carbonell and T.
		  M. Mitchell",
  title = 	 "Machine Learning: An Artificial Intelligence
		  Approach, Vol. I",
  publisher = 	 "Tioga",
  year = 	 "1983",
  address =	 "Palo Alto, CA"
}

@Book{DudaHart2nd,
  author =       "R. O. Duda and P. E. Hart and D. G. Stork",
  title =        "Pattern Classification",
  publisher =    "John Wiley and Sons",
  edition =      "2nd",
  year =         "2000"
}

@misc{anonymous,
  title= {Suppressed for Anonymity},
  author= {Author, N. N.},
  year= {2021}
}

@InCollection{Newell81,
  author =       "A. Newell and P. S. Rosenbloom",
  title =        "Mechanisms of Skill Acquisition and the Law of
                  Practice", 
  booktitle =    "Cognitive Skills and Their Acquisition",
  pages =        "1--51",
  publisher =    "Lawrence Erlbaum Associates, Inc.",
  year =         "1981",
  editor =       "J. R. Anderson",
  chapter =      "1",
  address =      "Hillsdale, NJ"
}


@Article{Samuel59,
  author = 	 "A. L. Samuel",
  title = 	 "Some Studies in Machine Learning Using the Game of
		  Checkers",
  journal =	 "IBM Journal of Research and Development",
  year =	 "1959",
  volume =	 "3",
  number =	 "3",
  pages =	 "211--229"
}

@article{lei2014distribution,
  title={Distribution-free prediction bands for non-parametric regression},
  author={Lei, Jing and Wasserman, Larry},
  journal={Journal of the Royal Statistical Society Series B: Statistical Methodology},
  volume={76},
  number={1},
  pages={71--96},
  year={2014},
  publisher={Oxford University Press}
}


@inproceedings{vovk2012conditional,
  title={Conditional validity of inductive conformal predictors},
  author={Vovk, Vladimir},
  booktitle={Asian conference on machine learning},
  pages={475--490},
  year={2012},
  organization={PMLR}
}


@article{lei2012distribution,
  title={Distribution free prediction bands},
  author={Lei, Jing and Wasserman, Larry},
  journal={arXiv preprint arXiv:1203.5422},
  year={2012}
}

@article{foygel2021limits,
  title={The limits of distribution-free conditional predictive inference},
  author={Foygel Barber, Rina and Candes, Emmanuel J and Ramdas, Aaditya and Tibshirani, Ryan J},
  journal={Information and Inference: A Journal of the IMA},
  volume={10},
  number={2},
  pages={455--482},
  year={2021},
  publisher={Oxford University Press}
}

@article{guan2019conformal,
  title={Conformal prediction with localization},
  author={Guan, Leying},
  journal={arXiv preprint arXiv:1908.08558},
  year={2019}
}

@article{romano2019conformalized,
  title={Conformalized quantile regression},
  author={Romano, Yaniv and Patterson, Evan and Candes, Emmanuel},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@article{guan2023localized,
  title={Localized conformal prediction: A generalized inference framework for conformal prediction},
  author={Guan, Leying},
  journal={Biometrika},
  volume={110},
  number={1},
  pages={33--50},
  year={2023},
  publisher={Oxford University Press}
}

@article{amoukou2023adaptive,
  title={Adaptive Conformal Prediction by Reweighting Nonconformity Score},
  author={Amoukou, Salim I and Brunel, Nicolas JB},
  journal={arXiv preprint arXiv:2303.12695},
  year={2023}
}


@article{han2022split,
  title={Split localized conformal prediction},
  author={Han, Xing and Tang, Ziyang and Ghosh, Joydeep and Liu, Qiang},
  journal={arXiv preprint arXiv:2206.13092},
  year={2022}
}

@article{papadopoulos2011regression,
  title={Regression conformal prediction with nearest neighbours},
  author={Papadopoulos, Harris and Vovk, Vladimir and Gammerman, Alexander},
  journal={Journal of Artificial Intelligence Research},
  volume={40},
  pages={815--840},
  year={2011}
}

@article{gibbs2023conformal,
  title={Conformal Prediction With Conditional Guarantees},
  author={Gibbs, Isaac and Cherian, John J and Cand{\`e}s, Emmanuel J},
  journal={arXiv preprint arXiv:2305.12616},
  year={2023}
}

@article{jung2022batch,
  title={Batch multivalid conformal prediction},
  author={Jung, Christopher and Noarov, Georgy and Ramalingam, Ramya and Roth, Aaron},
  journal={arXiv preprint arXiv:2209.15145},
  year={2022}
}

@article{bastani2022practical,
  title={Practical adversarial multivalid conformal prediction},
  author={Bastani, Osbert and Gupta, Varun and Jung, Christopher and Noarov, Georgy and Ramalingam, Ramya and Roth, Aaron},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={29362--29373},
  year={2022}
}

@article{romano2020malice,
  title={With malice toward none: Assessing uncertainty via equalized coverage},
  author={Romano, Yaniv and Barber, Rina Foygel and Sabatti, Chiara and Cand{\`e}s, Emmanuel},
  journal={Harvard Data Science Review},
  volume={2},
  number={2},
  pages={4},
  year={2020}
}

@article{vovk2003mondrian,
  title={Mondrian confidence machine},
  author={Vovk, Vladimir and Lindsay, David and Nouretdinov, Ilia and Gammerman, Alex},
  journal={Technical Report},
  year={2003}
}


@book{vovk2005algorithmic,
  title={Algorithmic learning in a random world},
  author={Vovk, Vladimir and Gammerman, Alexander and Shafer, Glenn},
  volume={29},
  year={2005},
  publisher={Springer}
}

@article{shafer2008tutorial,
  title={A Tutorial on Conformal Prediction.},
  author={Shafer, Glenn and Vovk, Vladimir},
  journal={Journal of Machine Learning Research},
  volume={9},
  number={3},
  year={2008}
}

@inproceedings{papadopoulos2002inductive,
  title={Inductive confidence machines for regression},
  author={Papadopoulos, Harris and Proedrou, Kostas and Vovk, Volodya and Gammerman, Alex},
  booktitle={Machine Learning: ECML 2002: 13th European Conference on Machine Learning Helsinki, Finland, August 19--23, 2002 Proceedings 13},
  pages={345--356},
  year={2002},
  organization={Springer}
}

@article{angelopoulos2021gentle,
  title={A gentle introduction to conformal prediction and distribution-free uncertainty quantification},
  author={Angelopoulos, Anastasios N and Bates, Stephen},
  journal={arXiv preprint arXiv:2107.07511},
  year={2021}
}



@article{stankeviciute2021conformal,
  title={Conformal time-series forecasting},
  author={Stankeviciute, Kamile and M Alaa, Ahmed and van der Schaar, Mihaela},
  journal={Advances in neural information processing systems},
  volume={34},
  pages={6216--6228},
  year={2021}
}


@inproceedings{seedat2023improving,
  title={Improving adaptive conformal prediction using self-supervised learning},
  author={Seedat, Nabeel and Jeffares, Alan and Imrie, Fergus and van der Schaar, Mihaela},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={10160--10177},
  year={2023},
  organization={PMLR}
}

@article{gibbs2021adaptive,
  title={Adaptive conformal inference under distribution shift},
  author={Gibbs, Isaac and Candes, Emmanuel},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={1660--1672},
  year={2021}
}

@article{barber2023conformal,
  title={Conformal prediction beyond exchangeability},
  author={Barber, Rina Foygel and Candes, Emmanuel J and Ramdas, Aaditya and Tibshirani, Ryan J},
  journal={The Annals of Statistics},
  volume={51},
  number={2},
  pages={816--845},
  year={2023},
  publisher={Institute of Mathematical Statistics}
}

@inproceedings{bostrom2021mondrian,
  title={Mondrian conformal predictive distributions},
  author={Bostr{\"o}m, Henrik and Johansson, Ulf and L{\"o}fstr{\"o}m, Tuwe},
  booktitle={Conformal and Probabilistic Prediction and Applications},
  pages={24--38},
  year={2021},
  organization={PMLR}
}

@article{gupta2020distribution,
  title={Distribution-free binary classification: prediction sets, confidence intervals and calibration},
  author={Gupta, Chirag and Podkopaev, Aleksandr and Ramdas, Aaditya},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={3711--3723},
  year={2020}
}

@article{sesia2021conformal,
  title={Conformal prediction using conditional histograms},
  author={Sesia, Matteo and Romano, Yaniv},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={6304--6315},
  year={2021}
}

@article{ghosh2023improving,
  title={Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis},
  author={Ghosh, Subhankar and Belkhouja, Taha and Yan, Yan and Doppa, Janardhan Rao},
  journal={arXiv preprint arXiv:2303.10694},
  year={2023}
}


@misc{misc_physicochemical_properties_of_protein_tertiary_structure_265,
  author       = {Rana,Prashant},
  title        = {{Physicochemical Properties of Protein Tertiary Structure}},
  year         = {2013},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C5QW3H}
}

@misc{misc_condition_based_maintenance_of_naval_propulsion_plants_316,
  author       = {Coraddu,Andrea and Oneto,Luca  and  Ghio,Alessandro  and  Savio,Stefano and  Anguita,Davide and Figari,Massimo},
  title        = {{Condition Based Maintenance of Naval Propulsion Plants}},
  year         = {2014},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C5K31K}
}

@misc{misc_combined_cycle_power_plant_294,
  author       = {Tfekci,Pnar and Kaya,Heysem},
  title        = {{Combined Cycle Power Plant}},
  year         = {2014},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C5002N}
}

@article{rasmussen1996delve,
  title={The DELVE manual},
  author={Rasmussen, Carl E and Neal, Radford M and Hinton, Geoffrey E and van Camp, Drew and Revow, Michael and Ghahramani, Zoubin and Kustra, R and Tibshirani, Robert},
  journal={URL http://www. cs. toronto. edu/\~{} delve},
  year={1996}
}

@article{corke1996robotics,
  title={A robotics toolbox for MATLAB},
  author={Corke, Peter I},
  journal={IEEE Robotics \& Automation Magazine},
  volume={3},
  number={1},
  pages={24--32},
  year={1996},
  publisher={IEEE}
}

@article{harrison1978hedonic,
  title={Hedonic housing prices and the demand for clean air},
  author={Harrison Jr, David and Rubinfeld, Daniel L},
  journal={Journal of environmental economics and management},
  volume={5},
  number={1},
  pages={81--102},
  year={1978},
  publisher={Elsevier}
}

@misc{misc_wine_quality_186,
  author       = {Cortez,Paulo and Cerdeira,A. and  Almeida,F. and  Matos,T. and Reis,J.},
  title        = {{Wine Quality}},
  year         = {2009},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C56S3T}
}

@misc{misc_energy_efficiency_242,
  author       = {Tsanas,Athanasios and Xifara,Angeliki},
  title        = {{Energy efficiency}},
  year         = {2012},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C51307}
}

@misc{misc_concrete_compressive_strength_165,
  author       = {Yeh,I-Cheng},
  title        = {{Concrete Compressive Strength}},
  year         = {2007},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C5PK67}
}

@misc{asuncion2007uci,
  title={UCI machine learning repository},
  author={Asuncion, Arthur and Newman, David},
  year={2007},
  publisher={Irvine, CA, USA}
}

@article{ke2017lightgbm,
  title={Lightgbm: A highly efficient gradient boosting decision tree},
  author={Ke, Guolin and Meng, Qi and Finley, Thomas and Wang, Taifeng and Chen, Wei and Ma, Weidong and Ye, Qiwei and Liu, Tie-Yan},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@inproceedings{akiba2019optuna,
  title={Optuna: A next-generation hyperparameter optimization framework},
  author={Akiba, Takuya and Sano, Shotaro and Yanase, Toshihiko and Ohta, Takeru and Koyama, Masanori},
  booktitle={Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery \& data mining},
  pages={2623--2631},
  year={2019}
}

@inproceedings{kivaranovic2020adaptive,
  title={Adaptive, distribution-free prediction intervals for deep networks},
  author={Kivaranovic, Danijel and Johnson, Kory D and Leeb, Hannes},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={4346--4356},
  year={2020},
  organization={PMLR}
}



@article{traag2019louvain,
  title={From Louvain to Leiden: guaranteeing well-connected communities},
  author={Traag, Vincent A and Waltman, Ludo and Van Eck, Nees Jan},
  journal={Scientific reports},
  volume={9},
  number={1},
  pages={5233},
  year={2019},
  publisher={Nature Publishing Group UK London}
}

@article{delvenne2010stability,
  title={Stability of graph communities across time scales},
  author={Delvenne, J-C and Yaliraki, Sophia N and Barahona, Mauricio},
  journal={Proceedings of the national academy of sciences},
  volume={107},
  number={29},
  pages={12755--12760},
  year={2010},
  publisher={National Acad Sciences}
}

@article{mao2022valid,
  title={Valid model-free spatial prediction},
  author={Mao, Huiying and Martin, Ryan and Reich, Brian J},
  journal={Journal of the American Statistical Association},
  pages={1--11},
  year={2022},
  publisher={Taylor \& Francis}
}

@article{meinshausen2006quantile,
  title={Quantile regression forests.},
  author={Meinshausen, Nicolai and Ridgeway, Greg},
  journal={Journal of machine learning research},
  volume={7},
  number={6},
  year={2006}
}