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Casey Jisoo Hong

dblp:222/7844 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Trustworthy machine learning · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Trustworthy machine learning › fairness › fairness auditing
algorithmic auditing		 0.312018
TuringBox: An Experimental Platform for the Evaluation of AI Systems · IJCAI 2018
Machine learning › Trustworthy machine learning
fairness		 0.312018
TuringBox: An Experimental Platform for the Evaluation of AI Systems · IJCAI 2018
Machine learning › Trustworthy machine learning
interpretability		 0.312018
TuringBox: An Experimental Platform for the Evaluation of AI Systems · IJCAI 2018
YearPublicationVenuePosition
2018 TuringBox: An Experimental Platform for the Evaluation of AI Systems
abstract
We introduce TuringBox, a platform to democratize the study of AI. On one side of the platform, AI contributors upload existing and novel algorithms to be studied scientifically by others. On the other side, AI examiners develop and post machine intelligence tasks to evaluate and characterize the outputs of algorithms. We outline the architecture of such a platform, and describe two interactive case studies of algorithmic auditing on the platform.
Ziv Epstein, Blakeley H. Payne, Judy Hanwen Shen, Casey Jisoo Hong, Bjarke Felbo, Abhimanyu Dubey, Matthew Groh, Nick Obradovich, Manuel Cebrián, Iyad Rahwan
 IJCAI4