-
Notifications
You must be signed in to change notification settings - Fork 0
/
bib.bib
3433 lines (3119 loc) · 160 KB
/
bib.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
@TechReport{xu2022conformal,
author = {Xu, Chen and Xie, Yao},
date = {2022-06},
institution = {arXiv},
title = {Conformal prediction set for time-series},
doi = {10.48550/arXiv.2206.07851},
note = {arXiv:2206.07851 [cs, stat] type: article},
url = {http://arxiv.org/abs/2206.07851},
urldate = {2023-07-22},
abstract = {When building either prediction intervals for regression (with real-valued response) or prediction sets for classification (with categorical responses), uncertainty quantification is essential to studying complex machine learning methods. In this paper, we develop Ensemble Regularized Adaptive Prediction Set (ERAPS) to construct prediction sets for time-series (with categorical responses), based on the prior work of [Xu and Xie, 2021]. In particular, we allow unknown dependencies to exist within features and responses that arrive in sequence. Method-wise, ERAPS is a distribution-free and ensemble-based framework that is applicable for arbitrary classifiers. Theoretically, we bound the coverage gap without assuming data exchangeability and show asymptotic set convergence. Empirically, we demonstrate valid marginal and conditional coverage by ERAPS, which also tends to yield smaller prediction sets than competing methods.},
annotation = {Comment: Strongly accepted by the Workshop on Distribution-Free Uncertainty Quantification at ICML 2022},
file = {arXiv Fulltext PDF:https\://arxiv.org/pdf/2206.07851.pdf:application/pdf},
keywords = {Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Methodology},
}
@Article{kingma2014adam,
author = {Kingma, Diederik P and Ba, Jimmy},
title = {Adam: A method for stochastic optimization},
journal = {arXiv preprint arXiv:1412.6980},
year = {2014},
}
@Misc{xiao2017fashion,
author = {Han Xiao and Kashif Rasul and Roland Vollgraf},
title = {Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms},
eprint = {1708.07747},
archiveprefix = {arXiv},
primaryclass = {cs.LG},
year = {2017},
}
@Online{mw2023fidelity,
author = {Merriam-Webster},
title = {"Fidelity"},
url = {https://www.merriam-webster.com/dictionary/fidelity},
language = {en},
organization = {Merriam-Webster},
urldate = {2023-03-23},
abstract = {the quality or state of being faithful; accuracy in details : exactness; the degree to which an electronic device (such as a record player, radio, or television) accurately reproduces its effect (such as sound or picture)… See the full definition},
}
@InProceedings{altmeyer2023endogenous,
author = {Altmeyer, Patrick and Angela, Giovan and Buszydlik, Aleksander and Dobiczek, Karol and van Deursen, Arie and Liem, Cynthia CS},
booktitle = {2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)},
title = {Endogenous Macrodynamics in Algorithmic Recourse},
organization = {IEEE},
pages = {418--431},
year = {2023},
}
%% 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},
title = {Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings},
doi = {10.2139/ssrn.195733},
number = {1},
pages = {91--117},
volume = {70},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Econometrica : journal of the Econometric Society},
shortjournal = {Econometrica},
year = {2002},
}
@Article{abadie2003economic,
author = {Abadie, Alberto and Gardeazabal, Javier},
title = {The Economic Costs of Conflict: {{A}} Case Study of the {{Basque Country}}},
number = {1},
pages = {113--132},
volume = {93},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {American economic review},
year = {2003},
}
@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}})},
title = {Machine {{Learning Model Drift Detection Via Weak Data Slices}}},
doi = {10.1109/deeptest52559.2021.00007},
pages = {1--8},
publisher = {{IEEE}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2021},
}
@Article{allen2017referencedependent,
author = {Allen, Eric J and Dechow, Patricia M and Pope, Devin G and Wu, George},
title = {Reference-Dependent Preferences: {{Evidence}} from Marathon Runners},
doi = {10.3386/w20343},
number = {6},
pages = {1657--1672},
volume = {63},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Management Science},
year = {2017},
}
@Article{altmeyer2018option,
author = {Altmeyer, Patrick and Grapendal, Jacob Daniel and Pravosud, Makar and Quintana, Gand Derry},
title = {Option Pricing in the {{Heston}} Stochastic Volatility Model: An Empirical Evaluation},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2018},
}
@Article{altmeyer2021deep,
author = {Altmeyer, Patrick and Agusti, Marc and Vidal-Quadras Costa, Ignacio},
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},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2021},
}
@Book{altmeyer2021deepvars,
author = {Altmeyer, Patrick},
title = {Deepvars: {{Deep Vector Autoregession}}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2021},
}
@Misc{altmeyer2022counterfactualexplanations,
author = {Altmeyer, Patrick},
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},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2022},
}
@Software{altmeyerCounterfactualExplanationsJlJulia2022,
author = {Altmeyer, Patrick},
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},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2022},
}
@Misc{angelopoulos2021gentle,
author = {Anastasios N. Angelopoulos and Stephen Bates},
title = {A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification},
eprint = {2107.07511},
archiveprefix = {arXiv},
primaryclass = {cs.LG},
year = {2022},
}
@Misc{angelopoulos2022uncertainty,
author = {Angelopoulos, Anastasios and Bates, Stephen and Malik, Jitendra and Jordan, Michael I.},
title = {Uncertainty {{Sets}} for {{Image Classifiers}} Using {{Conformal Prediction}}},
eprint = {2009.14193},
eprinttype = {arxiv},
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},
month = sep,
number = {arXiv:2009.14193},
primaryclass = {cs, math, stat},
publisher = {{arXiv}},
year = {2022},
}
@Article{angelucci2009indirect,
author = {Angelucci, Manuela and De Giorgi, Giacomo},
title = {Indirect Effects of an Aid Program: How Do Cash Transfers Affect Ineligibles' Consumption?},
doi = {10.1257/aer.99.1.486},
number = {1},
pages = {486--508},
volume = {99},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {American economic review},
year = {2009},
}
@Article{angrist1990lifetime,
author = {Angrist, Joshua D},
title = {Lifetime Earnings and the {{Vietnam}} Era Draft Lottery: Evidence from Social Security Administrative Records},
pages = {313--336},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {The American Economic Review},
year = {1990},
}
@Unpublished{antoran2020getting,
author = {Antor{\'a}n, Javier and Bhatt, Umang and Adel, Tameem and Weller, Adrian and Hern{\'a}ndez-Lobato, Jos{\'e} Miguel},
title = {Getting a Clue: {{A}} Method for Explaining Uncertainty Estimates},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2006.06848},
eprinttype = {arxiv},
year = {2020},
}
@Article{arcones1992bootstrap,
author = {Arcones, Miguel A and Gine, Evarist},
title = {On the Bootstrap of {{U}} and {{V}} Statistics},
pages = {655--674},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {The Annals of Statistics},
year = {1992},
}
@Article{ariely2003coherent,
author = {Ariely, Dan and Loewenstein, George and Prelec, Drazen},
title = {``{{Coherent}} Arbitrariness'': {{Stable}} Demand Curves without Stable Preferences},
doi = {10.1017/cbo9780511618031.014},
number = {1},
pages = {73--106},
volume = {118},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {The Quarterly journal of economics},
year = {2003},
}
@Article{ariely2006tom,
author = {Ariely, Dan and Loewenstein, George and Prelec, Drazen},
title = {Tom {{Sawyer}} and the Construction of Value},
doi = {10.1017/cbo9780511618031.015},
number = {1},
pages = {1--10},
volume = {60},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of Economic Behavior \& Organization},
year = {2006},
}
@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},
title = {Explainable {{Artificial Intelligence}} ({{XAI}}): {{Concepts}}, Taxonomies, Opportunities and Challenges toward Responsible {{AI}}},
doi = {10.1016/j.inffus.2019.12.012},
pages = {82--115},
volume = {58},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Information Fusion},
year = {2020},
}
@Article{auer2002finitetime,
author = {Auer, Peter and Cesa-Bianchi, Nicolo and Fischer, Paul},
title = {Finite-Time Analysis of the Multiarmed Bandit Problem},
number = {2},
pages = {235--256},
volume = {47},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Machine learning},
year = {2002},
}
@Article{barabasi2016network,
author = {Barab{\'a}si, Albert-L{\'a}szl{\'o}},
title = {Network {{Science}}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Network Science},
year = {2016},
}
@Unpublished{bastounis2021mathematics,
author = {Bastounis, Alexander and Hansen, Anders C and Vla{\v c}i{\'c}, Verner},
title = {The Mathematics of Adversarial Attacks in {{AI}}--{{Why}} Deep Learning Is Unstable despite the Existence of Stable Neural Networks},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2109.06098},
eprinttype = {arxiv},
year = {2021},
}
@Article{bechara1997deciding,
author = {Bechara, Antoine and Damasio, Hanna and Tranel, Daniel and Damasio, Antonio R},
title = {Deciding Advantageously before Knowing the Advantageous Strategy},
doi = {10.7551/mitpress/3077.003.0044},
number = {5304},
pages = {1293--1295},
volume = {275},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Science (New York, N.Y.)},
shortjournal = {Science},
year = {1997},
}
@Book{berlinet2011reproducing,
author = {Berlinet, Alain and Thomas-Agnan, Christine},
title = {Reproducing Kernel {{Hilbert}} Spaces in Probability and Statistics},
doi = {10.1007/978-1-4419-9096-9},
publisher = {{Springer Science \& Business Media}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2011},
}
@Misc{bernanke1990federal,
author = {Bernanke, Ben S},
title = {The Federal Funds Rate and the Channels of Monetary Transnission},
doi = {10.3386/w3487},
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}},
year = {1990},
}
@Article{besbes2014stochastic,
author = {Besbes, Omar and Gur, Yonatan and Zeevi, Assaf},
title = {Stochastic Multi-Armed-Bandit Problem with Non-Stationary Rewards},
pages = {199--207},
volume = {27},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Advances in neural information processing systems},
year = {2014},
}
@Article{bholat2020impact,
author = {Bholat, D and Gharbawi, M and Thew, O},
title = {The {{Impact}} of {{Covid}} on {{Machine Learning}} and {{Data Science}} in {{UK Banking}}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Bank of England Quarterly Bulletin, Q4},
year = {2020},
}
@Book{bishop2006pattern,
author = {Bishop, Christopher M},
title = {Pattern Recognition and Machine Learning},
publisher = {{springer}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2006},
}
@Article{blaom2020mlj,
author = {Blaom, Anthony D. and Kiraly, Franz and Lienart, Thibaut and Simillides, Yiannis and Arenas, Diego and Vollmer, Sebastian J.},
title = {{{MLJ}}: {{A Julia}} Package for Composable Machine Learning},
doi = {10.21105/joss.02704},
issn = {2475-9066},
number = {55},
pages = {2704},
urldate = {2022-10-27},
volume = {5},
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},
bdsk-url-1 = {https://joss.theoj.org/papers/10.21105/joss.02704},
bdsk-url-2 = {https://doi.org/10.21105/joss.02704},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
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:},
journal = {Journal of Open Source Software},
langid = {english},
month = nov,
shorttitle = {{{MLJ}}},
year = {2020},
}
@InProceedings{blundell2015weight,
author = {Blundell, Charles and Cornebise, Julien and Kavukcuoglu, Koray and Wierstra, Daan},
booktitle = {International Conference on Machine Learning},
title = {Weight Uncertainty in Neural Network},
pages = {1613--1622},
publisher = {{PMLR}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2015},
}
@Article{borch2022machine,
author = {Borch, Christian},
title = {Machine Learning, Knowledge Risk, and Principal-Agent Problems in Automated Trading},
doi = {10.1016/j.techsoc.2021.101852},
pages = {101852},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Technology in Society},
year = {2022},
}
@Article{borisov2022deep,
author = {Borisov, Vadim and Leemann, Tobias and Se{\ss}ler, Kathrin and Haug, Johannes and Pawelczyk, Martin and Kasneci, Gjergji},
title = {Deep neural networks and tabular data: A survey},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
publisher = {IEEE},
year = {2022},
}
@Article{bramoulle2009identification,
author = {Bramoull{\'e}, Yann and Djebbari, Habiba and Fortin, Bernard},
title = {Identification of Peer Effects through Social Networks},
doi = {10.2139/ssrn.965818},
number = {1},
pages = {41--55},
volume = {150},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of econometrics},
year = {2009},
}
@Article{bramoulle2020peer,
author = {Bramoull{\'e}, Yann and Djebbari, Habiba and Fortin, Bernard},
title = {Peer Effects in Networks: {{A}} Survey},
doi = {10.2139/ssrn.3534495},
pages = {603--629},
volume = {12},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Annual Review of Economics},
year = {2020},
}
@Unpublished{branco2015survey,
author = {Branco, Paula and Torgo, Luis and Ribeiro, Rita},
title = {A Survey of Predictive Modelling under Imbalanced Distributions},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {1505.01658},
eprinttype = {arxiv},
year = {2015},
}
@Book{brock1991nonlinear,
author = {Brock, William Allen and Brock, William A and Hsieh, David Arthur and LeBaron, Blake Dean and Brock, William E},
title = {Nonlinear Dynamics, Chaos, and Instability: Statistical Theory and Economic Evidence},
doi = {10.2307/2234554},
publisher = {{MIT press}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {1991},
}
@InProceedings{buolamwini2018gender,
author = {Buolamwini, Joy and Gebru, Timnit},
booktitle = {Conference on Fairness, Accountability and Transparency},
title = {Gender Shades: {{Intersectional}} Accuracy Disparities in Commercial Gender Classification},
pages = {77--91},
publisher = {{PMLR}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2018},
}
@Unpublished{bussmann2020neural,
author = {Bussmann, Bart and Nys, Jannes and Latr{\'e}, Steven},
title = {Neural {{Additive Vector Autoregression Models}} for {{Causal Discovery}} in {{Time Series Data}}},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2010.09429},
eprinttype = {arxiv},
year = {2020},
}
@Report{card1993minimum,
author = {Card, David and Krueger, Alan B},
title = {Minimum Wages and Employment: {{A}} Case Study of the Fast Food Industry in {{New Jersey}} and {{Pennsylvania}}},
doi = {10.3386/w4509},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
school = {{National Bureau of Economic Research}},
year = {1993},
}
@InProceedings{carlini2017evaluating,
author = {Carlini, Nicholas and Wagner, David},
booktitle = {2017 Ieee Symposium on Security and Privacy (Sp)},
title = {Towards Evaluating the Robustness of Neural Networks},
doi = {10.1109/sp.2017.49},
pages = {39--57},
publisher = {{IEEE}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2017},
}
@Article{carlisle2019racist,
author = {Carlisle, M.},
title = {Racist Data Destruction? - a {{Boston}} Housing Dataset Controversy},
url = {https://medium.com/@docintangible/racist-data-destruction-113e3eff54a8},
bdsk-url-1 = {https://medium.com/@docintangible/racist-data-destruction-113e3eff54a8},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2019},
}
@Article{carrell2009does,
author = {Carrell, Scott E and Fullerton, Richard L and West, James E},
title = {Does Your Cohort Matter? {{Measuring}} Peer Effects in College Achievement},
doi = {10.3386/w14032},
number = {3},
pages = {439--464},
volume = {27},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of Labor Economics},
year = {2009},
}
@Article{carrell2013natural,
author = {Carrell, Scott E and Sacerdote, Bruce I and West, James E},
title = {From Natural Variation to Optimal Policy? {{The}} Importance of Endogenous Peer Group Formation},
doi = {10.3982/ecta10168},
number = {3},
pages = {855--882},
volume = {81},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Econometrica : journal of the Econometric Society},
shortjournal = {Econometrica},
year = {2013},
}
@Article{carrizosa2021generating,
author = {Carrizosa, Emilio and Ramırez-Ayerbe, Jasone and Romero, Dolores},
title = {Generating {{Collective Counterfactual Explanations}} in {{Score-Based Classification}} via {{Mathematical Optimization}}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2021},
}
@Article{cascarino2022explainable,
author = {Cascarino, Giuseppe and Moscatelli, Mirko and Parlapiano, Fabio},
title = {Explainable {{Artificial Intelligence}}: Interpreting Default Forecasting Models Based on {{Machine Learning}}},
doi = {10.2139/ssrn.4090707},
number = {674},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Bank of Italy Occasional Paper},
year = {2022},
}
@Article{chandola2009anomaly,
author = {Chandola, Varun and Banerjee, Arindam and Kumar, Vipin},
title = {Anomaly Detection: {{A}} Survey},
number = {3},
pages = {1--58},
volume = {41},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {ACM computing surveys (CSUR)},
year = {2009},
}
@Article{chapelle2011empirical,
author = {Chapelle, Olivier and Li, Lihong},
title = {An Empirical Evaluation of Thompson Sampling},
pages = {2249--2257},
volume = {24},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Advances in neural information processing systems},
year = {2011},
}
@Article{chetty2011adjustment,
author = {Chetty, Raj and Friedman, John N and Olsen, Tore and Pistaferri, Luigi},
title = {Adjustment Costs, Firm Responses, and Micro vs. Macro Labor Supply Elasticities: {{Evidence}} from {{Danish}} Tax Records},
doi = {10.3386/w15617},
number = {2},
pages = {749--804},
volume = {126},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {The quarterly journal of economics},
year = {2011},
}
@Article{cortes1995supportvector,
author = {Cortes, Corinna and Vapnik, Vladimir},
title = {Support-Vector Networks},
number = {3},
pages = {273--297},
volume = {20},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Machine learning},
year = {1995},
}
@Article{crawford2019variable,
author = {Crawford, Lorin and Flaxman, Seth R and Runcie, Daniel E and West, Mike},
title = {Variable Prioritization in Nonlinear Black Box Methods: {{A}} Genetic Association Case Study},
doi = {10.1214/18-aoas1222},
number = {2},
pages = {958},
volume = {13},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {The annals of applied statistics},
year = {2019},
}
@InProceedings{dai2022counterfactual,
author = {Dai, Xinyue and Keane, Mark T and Shalloo, Laurence and Ruelle, Elodie and Byrne, Ruth MJ},
title = {Counterfactual Explanations for Prediction and Diagnosis in Xai},
doi = {10.1145/3514094.3534144},
eventtitle = {Proceedings of the 2022 {{AAAI}}/{{ACM Conference}} on {{AI}}, {{Ethics}}, and {{Society}}},
pages = {215--226},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2022},
}
@Article{danielsson2021artificial,
author = {Danielsson, Jon and Macrae, Robert and Uthemann, Andreas},
title = {Artificial Intelligence and Systemic Risk},
pages = {106290},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of Banking \& Finance},
year = {2021},
}
@Article{daxberger2021laplace,
author = {Daxberger, Erik and Kristiadi, Agustinus and Immer, Alexander and Eschenhagen, Runa and Bauer, Matthias and Hennig, Philipp},
title = {Laplace {{Redux-Effortless Bayesian Deep Learning}}},
volume = {34},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Advances in Neural Information Processing Systems},
year = {2021},
}
@Article{dehejia1999causal,
author = {Dehejia, Rajeev H and Wahba, Sadek},
title = {Causal Effects in Nonexperimental Studies: {{Reevaluating}} the Evaluation of Training Programs},
doi = {10.1080/01621459.1999.10473858},
number = {448},
pages = {1053--1062},
volume = {94},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of the American statistical Association},
year = {1999},
}
@Article{dell2010persistent,
author = {Dell, Melissa},
title = {The Persistent Effects of {{Peru}}'s Mining Mita},
doi = {10.2139/ssrn.1596425},
number = {6},
pages = {1863--1903},
volume = {78},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Econometrica : journal of the Econometric Society},
shortjournal = {Econometrica},
year = {2010},
}
@Article{denhengst2020reinforcement,
author = {den Hengst, Floris and Grua, Eoin Martino and el Hassouni, Ali and Hoogendoorn, Mark},
title = {Reinforcement Learning for Personalization: {{A}} Systematic Literature Review},
doi = {10.3233/ds-200028},
issue = {Preprint},
pages = {1--41},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Data Science},
options = {useprefix=true},
year = {2020},
}
@Article{deoliveira2021framework,
author = {de Oliveira, Raphael Mazzine Barbosa and Martens, David},
title = {A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data},
doi = {10.3390/app11167274},
number = {16},
pages = {7274},
volume = {11},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Applied Sciences},
options = {useprefix=true},
year = {2021},
}
@InProceedings{dombrowski2021diffeomorphic,
author = {Dombrowski, Ann-Kathrin and Gerken, Jan E and Kessel, Pan},
booktitle = {{{ICML Workshop}} on {{Invertible Neural Networks}}, {{Normalizing Flows}}, and {{Explicit Likelihood Models}}},
title = {Diffeomorphic Explanations with Normalizing Flows},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2021},
}
@InProceedings{dorffner1996neural,
author = {Dorffner, Georg},
booktitle = {Neural Network World},
title = {Neural Networks for Time Series Processing},
publisher = {{Citeseer}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {1996},
}
@Article{epstein1979stability,
author = {Epstein, Seymour},
title = {The Stability of Behavior: {{I}}. {{On}} Predicting Most of the People Much of the Time.},
doi = {10.1037/0022-3514.37.7.1097},
number = {7},
pages = {1097},
volume = {37},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of personality and social psychology},
year = {1979},
}
@Online{barocas2022fairness,
author = {Solon Barocas and Moritz Hardt and Arvind Narayanan},
title = {Fairness and Machine Learning},
url = {https://fairmlbook.org/index.html},
urldate = {2022-11-08},
bdsk-url-1 = {https://fairmlbook.org/index.html},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
month = dec,
year = {2022},
}
@Article{falk2006clean,
author = {Falk, Armin and Ichino, Andrea},
title = {Clean Evidence on Peer Effects},
doi = {10.1086/497818},
number = {1},
pages = {39--57},
volume = {24},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of labor economics},
year = {2006},
}
@Unpublished{fan2020interpretability,
author = {Fan, Fenglei and Xiong, Jinjun and Wang, Ge},
title = {On Interpretability of Artificial Neural Networks},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {2001.02522},
eprinttype = {arxiv},
year = {2020},
}
@Article{fang2011dynamic,
author = {Fang, Hanming and Gavazza, Alessandro},
title = {Dynamic Inefficiencies in an Employment-Based Health Insurance System: {{Theory}} and Evidence},
number = {7},
pages = {3047--77},
volume = {101},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {American Economic Review},
year = {2011},
}
@Article{fehr2000cooperation,
author = {Fehr, Ernst and Gachter, Simon},
title = {Cooperation and Punishment in Public Goods Experiments},
doi = {10.2139/ssrn.203194},
number = {4},
pages = {980--994},
volume = {90},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {American Economic Review},
year = {2000},
}
@Article{fix1951important,
author = {Fix, E and Hodges, J},
title = {An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation},
number = {57},
pages = {233--238},
volume = {3},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {International Statistical Review},
year = {1951},
}
@Book{friedman2008monetary,
author = {Friedman, Milton and Schwartz, Anna Jacobson},
title = {A Monetary History of the {{United States}}, 1867-1960},
publisher = {{Princeton University Press}},
volume = {14},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2008},
}
@InProceedings{gal2016dropout,
author = {Gal, Yarin and Ghahramani, Zoubin},
booktitle = {International Conference on Machine Learning},
title = {Dropout as a Bayesian Approximation: {{Representing}} Model Uncertainty in Deep Learning},
pages = {1050--1059},
publisher = {{PMLR}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2016},
}
@InProceedings{gal2017deep,
author = {Gal, Yarin and Islam, Riashat and Ghahramani, Zoubin},
booktitle = {International {{Conference}} on {{Machine Learning}}},
title = {Deep Bayesian Active Learning with Image Data},
pages = {1183--1192},
publisher = {{PMLR}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2017},
}
@Article{galizzi2019external,
author = {Galizzi, Matteo M and Navarro-Martinez, Daniel},
title = {On the External Validity of Social Preference Games: A Systematic Lab-Field Study},
doi = {10.1287/mnsc.2017.2908},
number = {3},
pages = {976--1002},
volume = {65},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Management Science},
year = {2019},
}
@Article{gama2014survey,
author = {Gama, Jo{\~a}o and {\v Z}liobait{\.e}, Indr{\.e} and Bifet, Albert and Pechenizkiy, Mykola and Bouchachia, Abdelhamid},
title = {A Survey on Concept Drift Adaptation},
number = {4},
pages = {1--37},
volume = {46},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {ACM computing surveys (CSUR)},
year = {2014},
}
@Unpublished{garivier2008upperconfidence,
author = {Garivier, Aur{\'e}lien and Moulines, Eric},
title = {On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {0805.3415},
eprinttype = {arxiv},
year = {2008},
}
@Book{gelman2013bayesian,
author = {Gelman, Andrew and Carlin, John B and Stern, Hal S and Dunson, David B and Vehtari, Aki and Rubin, Donald B},
title = {Bayesian Data Analysis},
publisher = {{CRC press}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2013},
}
@Article{gilbert1998immune,
author = {Gilbert, Daniel T and Pinel, Elizabeth C and Wilson, Timothy D and Blumberg, Stephen J and Wheatley, Thalia P},
title = {Immune Neglect: A Source of Durability Bias in Affective Forecasting.},
doi = {10.1037/0022-3514.75.3.617},
number = {3},
pages = {617},
volume = {75},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of personality and social psychology},
year = {1998},
}
@Article{gneezy2006uncertainty,
author = {Gneezy, Uri and List, John A and Wu, George},
title = {The Uncertainty Effect: {{When}} a Risky Prospect Is Valued Less than Its Worst Possible Outcome},
doi = {10.1093/qje/121.4.1283},
number = {4},
pages = {1283--1309},
volume = {121},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {The Quarterly Journal of Economics},
year = {2006},
}
@InCollection{goan2020bayesian,
author = {Goan, Ethan and Fookes, Clinton},
booktitle = {Case {{Studies}} in {{Applied Bayesian Data Science}}},
title = {Bayesian {{Neural Networks}}: {{An Introduction}} and {{Survey}}},
doi = {10.1007/978-3-030-42553-1_3},
pages = {45--87},
publisher = {{Springer}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2020},
}
@Article{goldsmith-pinkham2013social,
author = {Goldsmith-Pinkham, Paul and Imbens, Guido W},
title = {Social Networks and the Identification of Peer Effects},
number = {3},
pages = {253--264},
volume = {31},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of Business \& Economic Statistics},
year = {2013},
}
@Unpublished{goodfellow2014explaining,
author = {Goodfellow, Ian J and Shlens, Jonathon and Szegedy, Christian},
title = {Explaining and Harnessing Adversarial Examples},
archiveprefix = {arXiv},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
eprint = {1412.6572},
eprinttype = {arxiv},
year = {2014},
}
@Book{goodfellow2016deep,
author = {Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron},
title = {Deep {{Learning}}},
publisher = {{MIT Press}},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
year = {2016},
}
@Article{goodfriend2005incredible,
author = {Goodfriend, Marvin and King, Robert G},
title = {The Incredible {{Volcker}} Disinflation},
doi = {10.3386/w11562},
number = {5},
pages = {981--1015},
volume = {52},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Journal of Monetary Economics},
year = {2005},
}
@Article{graham2017econometric,
author = {Graham, Bryan S},
title = {An Econometric Model of Network Formation with Degree Heterogeneity},
doi = {10.1920/wp.cem.2017.0817},
number = {4},
pages = {1033--1063},
volume = {85},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Econometrica : journal of the Econometric Society},
shortjournal = {Econometrica},
year = {2017},
}
@Article{greene2012econometric,
author = {Greene, William H},
title = {Econometric Analysis, 71e},
date-added = {2022-12-13 12:58:01 +0100},
date-modified = {2022-12-13 12:58:01 +0100},
journal = {Stern School of Business, New York University},
year = {2012},
}
@Article{grether1979economic,
author = {Grether, David M and Plott, Charles R},
title = {Economic Theory of Choice and the Preference Reversal Phenomenon},
doi = {10.1017/cbo9780511618031.006},
number = {4},