Search Results for author: Joshua Lee

Found 5 papers, 2 papers with code

A Maximal Correlation Framework for Fair Machine Learning

no code implementations Entropy 2022 Joshua Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky and Rogerio Schmidt Feris

As machine learning algorithms grow in popularity and diversify to many industries, ethical and legal concerns regarding their fairness have become increasingly relevant.

Fairness

A Maximal Correlation Approach to Imposing Fairness in Machine Learning

no code implementations30 Dec 2020 Joshua Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory Wornell, Leonid Karlinsky, Rogerio Feris

As machine learning algorithms grow in popularity and diversify to many industries, ethical and legal concerns regarding their fairness have become increasingly relevant.

BIG-bench Machine Learning Fairness

Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration

1 code implementation3 Aug 2020 Joshua Lee, Jeffrey Fong, Bing Cai Kok, Harold Soh

Common experience suggests that agents who know each other well are better able to work together.

Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks

no code implementations NeurIPS 2019 Joshua Lee, Prasanna Sattigeri, Gregory Wornell

However, for practical, privacy, or other reasons, in a variety of applications we may have no control over the individual source task training, nor access to source training samples.

Transfer Learning

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