fairness haverford.edu

On algorithmic fairness, discrimination and disparate impact.

A collection of articles and research on the problems of fairness in algorithms.
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This web page fairness.haverford.edu presently has an average traffic classification of zero (the lower the superior). We have probed one page inside the website fairness.haverford.edu and found six websites associating themselves with fairness.haverford.edu.
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6

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LINKS TO WEB SITE

Toshihiro Kamishima

My research interests are machine learning and data mining, in particular fairness-aware data mining. AIST Tsukuba Central 2, Umezono 1-1-1, Tsukuba, Ibaraki, 305-8568 Japan.

The Geomblog

Ruminations on computational geometry, algorithms, theoretical computer science and life. A conceptual view of clustering. Tuesday, July 28, 2015. From MSR New York, Sorelle Friedler. From Haverford College, Mykola Pechenizkiy.

Seth V. Neel PhD student in Statistics, The Wharton School, UPenn.

PhD student in Statistics, The Wharton School, UPenn. Are mapped to an intermediate representation.

WHAT DOES FAIRNESS.HAVERFORD.EDU LOOK LIKE?

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FAIRNESS.HAVERFORD.EDU HOST

I diagnosed that a single root page on fairness.haverford.edu took one hundred and forty-two milliseconds to come up. I could not detect a SSL certificate, so our web crawlers consider fairness.haverford.edu not secure.
Load time
0.142 secs
SSL
NOT SECURE
Internet Protocol
165.82.168.3

WEBSITE IMAGE

SERVER OS AND ENCODING

I diagnosed that this domain is utilizing the nginx/1.4.6 (Ubuntu) os.

PAGE TITLE

On algorithmic fairness, discrimination and disparate impact.

DESCRIPTION

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

CONTENT

This web page states the following, "On algorithmic fairness, discrimination and disparate impact." We viewed that the web page also stated " What is algorithmic fairness and why is it important? This site serves to collect articles and research that will help to answer these questions." It also said " Our own take on the research questions behind these issues can be found in this paper. More research is collected at fatml. Cynthia Dwork in the NYT on algorithmic fairness. A review of the panel discussion at FATML 2."

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