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ORCID1st FORC 2020: Cambridge, MA, USA [virtual conference]
- Aaron Roth:
1st Symposium on Foundations of Responsible Computing, FORC 2020, June 1-3, 2020, Harvard University, Cambridge, MA, USA (virtual conference). LIPIcs 156, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2020, ISBN 978-3-95977-142-9 - Front Matter, Table of Contents, Preface, Conference Organization. 0:1-0:8
- Lee Cohen, Zachary C. Lipton, Yishay Mansour:
Efficient Candidate Screening Under Multiple Tests and Implications for Fairness. 1:1-1:20 - Christina Ilvento:
Metric Learning for Individual Fairness. 2:1-2:11 - Avrim Blum
, Kevin Stangl:
Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? 3:1-3:20 - Moni Naor, Neil Vexler:
Can Two Walk Together: Privacy Enhancing Methods and Preventing Tracking of Users. 4:1-4:20 - Christopher Jung, Sampath Kannan, Neil Lutz:
Service in Your Neighborhood: Fairness in Center Location. 5:1-5:15 - Ashesh Rambachan, Jonathan Roth:
Bias In, Bias Out? Evaluating the Folk Wisdom. 6:1-6:15 - Cynthia Dwork, Christina Ilvento, Meena Jagadeesan:
Individual Fairness in Pipelines. 7:1-7:22 - Cynthia Dwork, Christina Ilvento, Guy N. Rothblum, Pragya Sur:
Abstracting Fairness: Oracles, Metrics, and Interpretability. 8:1-8:16 - Mark Braverman, Sumegha Garg:
The Role of Randomness and Noise in Strategic Classification. 9:1-9:20 - Katrina Ligett, Charlotte Peale, Omer Reingold:
Bounded-Leakage Differential Privacy. 10:1-10:20
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