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@InProceedings{altmeyer2023endogenous,
author = {Altmeyer, Patrick and Angela, Giovan and Buszydlik, Aleksander and Dobiczek, Karol and van Deursen, Arie and Liem, Cynthia},
booktitle = {First {IEEE} {Conference} on {Secure} and {Trustworthy} {Machine} {Learning}},
date = {2023},
title = {Endogenous {Macrodynamics} in {Algorithmic} {Recourse}},
file = {:altmeyerendogenous - Endogenous Macrodynamics in Algorithmic Recourse.pdf:PDF},
}
%% This BibTeX bibliography file was created using BibDesk.
%% https://bibdesk.sourceforge.io/
%% Created for Patrick Altmeyer at 2022-12-13 12:58:22 +0100
%% Saved with string encoding Unicode (UTF-8)
@article{abadie2002instrumental,
author = {Abadie, Alberto and Angrist, Joshua and Imbens, Guido},
date = {2002},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Econometrica : journal of the Econometric Society},
number = {1},
pages = {91--117},
shortjournal = {Econometrica},
title = {Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings},
volume = {70}}
@article{abadie2003economic,
author = {Abadie, Alberto and Gardeazabal, Javier},
date = {2003},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {American economic review},
number = {1},
pages = {113--132},
title = {The Economic Costs of Conflict: {{A}} Case Study of the {{Basque Country}}},
volume = {93}}
@inproceedings{ackerman2021machine,
author = {Ackerman, Samuel and Dube, Parijat and Farchi, Eitan and Raz, Orna and Zalmanovici, Marcel},
booktitle = {2021 {{IEEE}}/{{ACM Third International Workshop}} on {{Deep Learning}} for {{Testing}} and {{Testing}} for {{Deep Learning}} ({{DeepTest}})},
date = {2021},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
pages = {1--8},
publisher = {{IEEE}},
title = {Machine {{Learning Model Drift Detection Via Weak Data Slices}}}}
@article{allen2017referencedependent,
author = {Allen, Eric J and Dechow, Patricia M and Pope, Devin G and Wu, George},
date = {2017},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Management Science},
number = {6},
pages = {1657--1672},
title = {Reference-Dependent Preferences: {{Evidence}} from Marathon Runners},
volume = {63}}
@article{altmeyer2018option,
author = {Altmeyer, Patrick and Grapendal, Jacob Daniel and Pravosud, Makar and Quintana, Gand Derry},
date = {2018},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
title = {Option Pricing in the {{Heston}} Stochastic Volatility Model: An Empirical Evaluation}}
@article{altmeyer2021deep,
author = {Altmeyer, Patrick and Agusti, Marc and Vidal-Quadras Costa, Ignacio},
date = {2021},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
title = {Deep {{Vector Autoregression}} for {{Macroeconomic Data}}},
url = {https://thevoice.bse.eu/wp-content/uploads/2021/07/ds21-project-agusti-et-al.pdf},
bdsk-url-1 = {https://thevoice.bse.eu/wp-content/uploads/2021/07/ds21-project-agusti-et-al.pdf}}
@book{altmeyer2021deepvars,
author = {Altmeyer, Patrick},
date = {2021},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
title = {Deepvars: {{Deep Vector Autoregession}}}}
@misc{altmeyer2022counterfactualexplanations,
author = {Altmeyer, Patrick},
date = {2022},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
title = {{{CounterfactualExplanations}}.Jl - a {{Julia}} Package for {{Counterfactual Explanations}} and {{Algorithmic Recourse}}},
url = {https://github.com/pat-alt/CounterfactualExplanations.jl},
bdsk-url-1 = {https://github.com/pat-alt/CounterfactualExplanations.jl}}
@software{altmeyerCounterfactualExplanationsJlJulia2022,
author = {Altmeyer, Patrick},
date = {2022},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
title = {{{CounterfactualExplanations}}.Jl - a {{Julia}} Package for {{Counterfactual Explanations}} and {{Algorithmic Recourse}}},
url = {https://github.com/pat-alt/CounterfactualExplanations.jl},
version = {0.1.2},
bdsk-url-1 = {https://github.com/pat-alt/CounterfactualExplanations.jl}}
@unpublished{angelopoulos2021gentle,
archiveprefix = {arXiv},
author = {Angelopoulos, Anastasios N. and Bates, Stephen},
date = {2021},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2107.07511},
eprinttype = {arxiv},
file = {/Users/FA31DU/Zotero/storage/RKSUMYZG/Angelopoulos and Bates - 2021 - A gentle introduction to conformal prediction and .pdf;/Users/FA31DU/Zotero/storage/PRUEKRR3/2107.html},
title = {A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification}}
@Misc{angelopoulos2022uncertainty,
author = {Angelopoulos, Anastasios and Bates, Stephen and Malik, Jitendra and Jordan, Michael I.},
date = {2022-09-03},
title = {Uncertainty {{Sets}} for {{Image Classifiers}} Using {{Conformal Prediction}}},
eprint = {2009.14193},
eprinttype = {arxiv},
url = {http://arxiv.org/abs/2009.14193},
urldate = {2022-12-07},
abstract = {Convolutional image classifiers can achieve high predictive accuracy, but quantifying their uncertainty remains an unresolved challenge, hindering their deployment in consequential settings. Existing uncertainty quantification techniques, such as Platt scaling, attempt to calibrate the network's probability estimates, but they do not have formal guarantees. We present an algorithm that modifies any classifier to output a predictive set containing the true label with a user-specified probability, such as 90\%. The algorithm is simple and fast like Platt scaling, but provides a formal finite-sample coverage guarantee for every model and dataset. Our method modifies an existing conformal prediction algorithm to give more stable predictive sets by regularizing the small scores of unlikely classes after Platt scaling. In experiments on both Imagenet and Imagenet-V2 with ResNet-152 and other classifiers, our scheme outperforms existing approaches, achieving coverage with sets that are often factors of 5 to 10 smaller than a stand-alone Platt scaling baseline.},
archiveprefix = {arXiv},
bdsk-url-1 = {http://arxiv.org/abs/2009.14193},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
file = {/Users/FA31DU/Zotero/storage/5BYIRBR2/Angelopoulos et al. - 2022 - Uncertainty Sets for Image Classifiers using Confo.pdf;/Users/FA31DU/Zotero/storage/2QJAKFKV/2009.html},
keywords = {Computer Science - Computer Vision and Pattern Recognition, Mathematics - Statistics Theory, Statistics - Machine Learning},
number = {arXiv:2009.14193},
primaryclass = {cs, math, stat},
publisher = {{arXiv}},
}
@article{angelucci2009indirect,
author = {Angelucci, Manuela and De Giorgi, Giacomo},
date = {2009},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {American economic review},
number = {1},
pages = {486--508},
title = {Indirect Effects of an Aid Program: How Do Cash Transfers Affect Ineligibles' Consumption?},
volume = {99}}
@article{angrist1990lifetime,
author = {Angrist, Joshua D},
date = {1990},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {The American Economic Review},
pages = {313--336},
title = {Lifetime Earnings and the {{Vietnam}} Era Draft Lottery: Evidence from Social Security Administrative Records}}
@unpublished{antoran2020getting,
archiveprefix = {arXiv},
author = {Antor{\'a}n, Javier and Bhatt, Umang and Adel, Tameem and Weller, Adrian and Hern{\'a}ndez-Lobato, Jos{\'e} Miguel},
date = {2020},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2006.06848},
eprinttype = {arxiv},
title = {Getting a Clue: {{A}} Method for Explaining Uncertainty Estimates}}
@article{arcones1992bootstrap,
author = {Arcones, Miguel A and Gine, Evarist},
date = {1992},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {The Annals of Statistics},
pages = {655--674},
title = {On the Bootstrap of {{U}} and {{V}} Statistics}}
@article{ariely2003coherent,
author = {Ariely, Dan and Loewenstein, George and Prelec, Drazen},
date = {2003},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {The Quarterly journal of economics},
number = {1},
pages = {73--106},
title = {``{{Coherent}} Arbitrariness'': {{Stable}} Demand Curves without Stable Preferences},
volume = {118}}
@article{ariely2006tom,
author = {Ariely, Dan and Loewenstein, George and Prelec, Drazen},
date = {2006},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Journal of Economic Behavior \& Organization},
number = {1},
pages = {1--10},
title = {Tom {{Sawyer}} and the Construction of Value},
volume = {60}}
@article{arrieta2020explainable,
author = {Arrieta, Alejandro Barredo and Diaz-Rodriguez, Natalia and Del Ser, Javier and Bennetot, Adrien and Tabik, Siham and Barbado, Alberto and Garcia, Salvador and Gil-Lopez, Sergio and Molina, Daniel and Benjamins, Richard and others},
date = {2020},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Information Fusion},
pages = {82--115},
title = {Explainable {{Artificial Intelligence}} ({{XAI}}): {{Concepts}}, Taxonomies, Opportunities and Challenges toward Responsible {{AI}}},
volume = {58}}
@article{auer2002finitetime,
author = {Auer, Peter and Cesa-Bianchi, Nicolo and Fischer, Paul},
date = {2002},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Machine learning},
number = {2},
pages = {235--256},
title = {Finite-Time Analysis of the Multiarmed Bandit Problem},
volume = {47}}
@article{barabasi2016network,
author = {Barab{\'a}si, Albert-L{\'a}szl{\'o}},
date = {2016},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Network Science},
title = {Network {{Science}}}}
@unpublished{bastounis2021mathematics,
archiveprefix = {arXiv},
author = {Bastounis, Alexander and Hansen, Anders C and Vla{\v c}i{\'c}, Verner},
date = {2021},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2109.06098},
eprinttype = {arxiv},
title = {The Mathematics of Adversarial Attacks in {{AI}}--{{Why}} Deep Learning Is Unstable despite the Existence of Stable Neural Networks}}
@article{bechara1997deciding,
author = {Bechara, Antoine and Damasio, Hanna and Tranel, Daniel and Damasio, Antonio R},
date = {1997},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Science (New York, N.Y.)},
number = {5304},
pages = {1293--1295},
shortjournal = {Science},
title = {Deciding Advantageously before Knowing the Advantageous Strategy},
volume = {275}}
@book{berlinet2011reproducing,
author = {Berlinet, Alain and Thomas-Agnan, Christine},
date = {2011},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
publisher = {{Springer Science \& Business Media}},
title = {Reproducing Kernel {{Hilbert}} Spaces in Probability and Statistics}}
@misc{bernanke1990federal,
author = {Bernanke, Ben S},
date = {1990},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
publisher = {{National Bureau of Economic Research Cambridge, Mass., USA}},
title = {The Federal Funds Rate and the Channels of Monetary Transnission}}
@article{besbes2014stochastic,
author = {Besbes, Omar and Gur, Yonatan and Zeevi, Assaf},
date = {2014},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Advances in neural information processing systems},
pages = {199--207},
title = {Stochastic Multi-Armed-Bandit Problem with Non-Stationary Rewards},
volume = {27}}
@article{bholat2020impact,
author = {Bholat, D and Gharbawi, M and Thew, O},
date = {2020},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journaltitle = {Bank of England Quarterly Bulletin, Q4},
title = {The {{Impact}} of {{Covid}} on {{Machine Learning}} and {{Data Science}} in {{UK Banking}}}}
@book{bishop2006pattern,
author = {Bishop, Christopher M},
date = {2006},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
publisher = {{springer}},
title = {Pattern Recognition and Machine Learning}}
@article{blaom2020mlj,
abstract = {Blaom et al., (2020). MLJ: A Julia package for composable machine learning. Journal of Open Source Software, 5(55), 2704, https://doi.org/10.21105/joss.02704},
author = {Blaom, Anthony D. and Kiraly, Franz and Lienart, Thibaut and Simillides, Yiannis and Arenas, Diego and Vollmer, Sebastian J.},
date = {2020-11-07},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
doi = {10.21105/joss.02704},
file = {/Users/FA31DU/Zotero/storage/7AY87FGP/Blaom et al. - 2020 - MLJ A Julia package for composable machine learni.pdf;/Users/FA31DU/Zotero/storage/D69YSMVF/joss.html},
issn = {2475-9066},
journaltitle = {Journal of Open Source Software},
langid = {english},
number = {55},
pages = {2704},
shorttitle = {{{MLJ}}},
title = {{{MLJ}}: {{A Julia}} Package for Composable Machine Learning},
url = {https://joss.theoj.org/papers/10.21105/joss.02704},
urldate = {2022-10-27},
volume = {5},
bdsk-url-1 = {https://joss.theoj.org/papers/10.21105/joss.02704},
bdsk-url-2 = {https://doi.org/10.21105/joss.02704}}
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