Report outline added

paper/biblio.bib

+%% This BibTeX bibliography file was created using BibDesk.
+%% http://bibdesk.sourceforge.net/
+
+%% Created for Laine, Riku P at 2019-08-02 09:38:23 +0300 
+
+
+%% Saved with string encoding Unicode (UTF-8) 
+
+
+
+@inproceedings{tolan2019why,
+	Acmid = {3326705},
+	Address = {New York, NY, USA},
+	Author = {Tolan, Song\"{u}l and Miron, Marius and G\'{o}mez, Emilia and Castillo, Carlos},
+	Booktitle = {Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law},
+	Date-Added = {2019-08-02 06:37:23 +0000},
+	Date-Modified = {2019-08-02 06:38:23 +0000},
+	Doi = {10.1145/3322640.3326705},
+	Isbn = {978-1-4503-6754-7},
+	Keywords = {algorithmic bias, algorithmic fairness, criminal recidivism, machine learning, risk assessment},
+	Location = {Montreal, QC, Canada},
+	Numpages = {10},
+	Pages = {83--92},
+	Publisher = {ACM},
+	Series = {ICAIL '19},
+	Title = {Why Machine Learning May Lead to Unfairness: Evidence from Risk Assessment for Juvenile Justice in Catalonia},
+	Url = {http://doi.acm.org/10.1145/3322640.3326705},
+	Year = {2019},
+	Bdsk-Url-1 = {http://doi.acm.org/10.1145/3322640.3326705},
+	Bdsk-Url-2 = {http://dx.doi.org/10.1145/3322640.3326705}}
+
+@article{pearl2010introduction,
+	Author = {Pearl, Judea},
+	Date-Added = {2019-08-02 06:37:23 +0000},
+	Date-Modified = {2019-08-02 06:37:23 +0000},
+	Journal = {The international journal of biostatistics},
+	Number = {2},
+	Publisher = {De Gruyter},
+	Title = {An introduction to causal inference},
+	Volume = {6},
+	Year = {2010}}
+
 @inproceedings{lakkaraju2017selective,
-  title={The selective labels problem: Evaluating algorithmic predictions in the presence of unobservables},
-  author={Lakkaraju, Himabindu and Kleinberg, Jon and Leskovec, Jure and Ludwig, Jens and Mullainathan, Sendhil},
-  booktitle={Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
-  pages={275--284},
-  year={2017},
-  organization={ACM}
-}
+	Acmid = {3098066},
+	Address = {New York, NY, USA},
+	Author = {Lakkaraju, Himabindu and Kleinberg, Jon and Leskovec, Jure and Ludwig, Jens and Mullainathan, Sendhil},
+	Booktitle = {Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
+	Date-Added = {2019-08-02 06:37:23 +0000},
+	Date-Modified = {2019-08-02 06:37:23 +0000},
+	Doi = {10.1145/3097983.3098066},
+	Isbn = {978-1-4503-4887-4},
+	Keywords = {evaluating machine learning algorithms, selective labels, unmeasured confounders, unobservables},
+	Location = {Halifax, NS, Canada},
+	Numpages = {10},
+	Pages = {275--284},
+	Publisher = {ACM},
+	Series = {KDD '17},
+	Title = {The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables},
+	Url = {http://doi.acm.org/10.1145/3097983.3098066},
+	Year = {2017},
+	Bdsk-Url-1 = {http://doi.acm.org/10.1145/3097983.3098066},
+	Bdsk-Url-2 = {http://dx.doi.org/10.1145/3097983.3098066}}
+
+@article{jung2018algorithmic,
+	Author = {Jung, Jongbin and Shroff, Ravi and Feller, Avi and Goel, Sharad},
+	Date-Added = {2019-08-02 06:37:23 +0000},
+	Date-Modified = {2019-08-02 06:37:23 +0000},
+	Journal = {arXiv preprint arXiv:1805.01868},
+	Title = {Algorithmic decision making in the presence of unmeasured confounding},
+	Year = {2018}}
+
+@article{dearteaga2018learning,
+	Author = {De-Arteaga, Maria and Dubrawski, Artur and Chouldechova, Alexandra},
+	Date-Added = {2019-08-02 06:37:23 +0000},
+	Date-Modified = {2019-08-02 06:37:23 +0000},
+	Journal = {arXiv preprint arXiv:1807.00905},
+	Title = {Learning under selective labels in the presence of expert consistency},
+	Year = {2018}}

paper/macros.tex

@@ -45,6 +45,10 @@
 \newcommand{\outcome}{\ensuremath{Y}\xspace}
 \newcommand{\outcomeValue}{\ensuremath{y}\xspace}
 \newcommand{\doop}[1]{\ensuremath{\mathbf{do}(#1)}}
+\newcommand{\unobservable}{\ensuremath{Z}\xspace}
+\newcommand{\unobservableValue}{\ensuremath{z}\xspace}
+\newcommand{\invlogit}{\text{logit}^{-1}}
+
 
 \newcommand{\generalPerformance}{\ensuremath{\mathbf{gp}}\xspace}
 \newcommand{\empiricalPerformance}{\ensuremath{\mathbf{ep}}\xspace}