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fairness.haverford.edu

On algorithmic fairness, discrimination and disparate impact.

A collection of articles and research on the problems of fairness in algorithms.

http://fairness.haverford.edu/

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On algorithmic fairness, discrimination and disparate impact. | fairness.haverford.edu Reviews
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On algorithmic fairness, discrimination and disparate impact. | fairness.haverford.edu Reviews

https://fairness.haverford.edu

A collection of articles and research on the problems of fairness in algorithms.

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fairness.haverford.edu fairness.haverford.edu
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On algorithmic fairness, discrimination and disparate impact.

http://fairness.haverford.edu/jekyll

On algorithmic fairness, discrimination, and disparate impact. What is algorithmic fairness and why is it important? This site serves to collect articles and research that will help to answer these questions. Our own take on the research questions behind these issues can be found in this paper. More research is collected at fatml.org. Could your data discriminate? Our entry in the Knight News Challenge. Stay tuned!

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kamishima.net kamishima.net

Fairness-Aware Data Mining | Toshihiro Kamishima

http://www.kamishima.net/fadm

Soft & Data. Soft & Data. The goal of fairness-aware data mining is to analyze data while taking into account potential issues of fairness, discrimination, neutrality, and/or independence. Pedreschi, Ruggieri, and Turini in KDD2008. Firstly posed this problem, and a literature about this topic was emerged. General discussion about fairness-aware data mining. Future Directions of Fairness-aware Data Mining: Recommendation, Causality, and Theoretical Aspects ICMLW15. Links to Related Sites. We stated a fai...

blog.geomblog.org blog.geomblog.org

The Geomblog: 02/01/2015 - 03/01/2015

http://blog.geomblog.org/2015_02_01_archive.html

Ruminations on computational geometry, algorithms, theoretical computer science and life. The Job Search: A series of posts. Clustering: A conceptual approach. Sunday, February 22, 2015. STOC 2015 Call for Workshops and Tutorials. I've had two week from hell with proposal deadlines, paper deadlines, faculty candidates and. Ever-more demanding hungry cries of the baby chickadees. Meetings with my students. Will have a workshops and tutorials day. Are running the event, and they want your proposals. If ove...

blog.geomblog.org blog.geomblog.org

The Geomblog: Racism/sexism in algorithms

http://blog.geomblog.org/2015/07/racismsexism-in-algorithms.html

Ruminations on computational geometry, algorithms, theoretical computer science and life. The Job Search: A series of posts. Clustering: A conceptual approach. Friday, July 24, 2015. For my sins, or more specifically because of my interest in fairness. I was asked to be on a panel discussing algorithmic racism/bias on The Stream. A web/tv show on Al Jazeera English (as opposed to Al Jazeera America, in case you're not already confused). Posted by Suresh Venkatasubramanian. Disqus for The Geomblog.

sethstatistics.wordpress.com sethstatistics.wordpress.com

About – Seth V. Neel

https://sethstatistics.wordpress.com/about

Seth V. Neel. PhD student in Statistics, The Wharton School, UPenn. I’m a second year statistics. Doctoral candidate at The Wharton School, University of Pennsylvania. Although my degree is in statistics, I am in the uniquely fortunate position of being advised by Michael Kearns. Both housed in the University of Pennsylvania Computer Science Department. I graduated from Harvard. In May 2015, with a degree in mathematics. My research is in theoretical machine learning. In Fall 2016, I was the head TA for.

blog.geomblog.org blog.geomblog.org

The Geomblog: 07/01/2015 - 08/01/2015

http://blog.geomblog.org/2015_07_01_archive.html

Ruminations on computational geometry, algorithms, theoretical computer science and life. The Job Search: A series of posts. Clustering: A conceptual approach. Tuesday, July 28, 2015. The 2nd Workshop on Fairness, Accuracy and Transparency in Machine Learning: A review. I was one of the organizers of the 2nd workshop on Fairness, Accuracy and Transparency in Machine Learning (FATML). From MSR New York, Sorelle Friedler. From Haverford College, Mykola Pechenizkiy. From UMass-Amherst and MSR. On the differ...

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On algorithmic fairness, discrimination and disparate impact.

On algorithmic fairness, discrimination and disparate impact. What is algorithmic fairness and why is it important? This site serves to collect articles and research that will help to answer these questions. Our own take on the research questions behind these issues can be found in this paper. More research is collected at fatml.org. Aug 12, 2015. Cynthia Dwork in the NYT on algorithmic fairness. Jul 28, 2015. A review of the panel discussion at FATML 2. Jul 28, 2015. Jul 28, 2015. Jul 24, 2015. A collec...

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In A Sentence .org. The best little site that helps you understand word usage with examples. Fairness in a sentence. Cabanas perspective on things, in fairness, is a symptom, not the disease itself. Obama used the word fairness in his third State of the Union. Well show you why some are pushing for what they call fairness on the air. He wanted to reduce the number of illegal aliens eligible for amnesty and to instill what he called fairness into the legislation. Use budged in a sentence. CARL PALADINO: I...

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