A technique to improve both fairness and accuracy in ...

A technique to improve both fairness and accuracy in ... - MIT News

MIT researchers analyzed a technique designed to improve a machine-learning model's overall accuracy, and found that it causes the model to ...

A technique to improve AI fairness and accuracy - INDIAai

Users sometimes use a method called "selective regression," in which the model figures out how sure it is about each prediction and rejects ...

A technique to improve both fairness and accuracy in artificial ...

Methods that make a machine-learning model's predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.

Jayant Sahu on LinkedIn: A technique to improve both fairness and ...

A technique to improve both fairness and accuracy in artificial intelligence.

"MACHINE LEARNING METHODS TO IMPROVE FAIRNESS AND ...

In this dissertation, we have focused on fairness and accuracy embodied in such predictions. ... In this dissertation we develop machine learning methods to ...

MIT Researchers Develop a Technique to Improve Fairness and ...

MIT Researchers Develop a Technique to Improve Fairness and Accuracy in a Machine Learning Model. ... The researchers developed two NN ...

Improving fairness in personalized AI models

Lin's paper, Fair Collaborative Learning (FairCL): A Method to Improve Fairness ... improve both the accuracy and fairness of personalized models.

Sensitive loss: Improving accuracy and fairness of face ...

We propose a discrimination-aware learning method to improve both the accuracy and fairness of biased face recognition algorithms.

A technique to improve both fairness and accuracy in artificial ...

610K subscribers in the ArtificialInteligence community. The goal of the r/ArtificialIntelligence is to provide a gateway to the many different…

Highlands India - A technique to improve both fairness and accuracy ...

A technique to improve both fairness and accuracy in artificial intelligence For people who use machine-learning models to help them make decisions,...

Strategies to improve fairness in artificial intelligence:A systematic ...

Generally, techniques to promote fairness can be implemented in the following stages of the AI process: preprocessing, processing (also ...

Search-based Automatic Repair for Fairness and Accuracy in ... - NCBI

However, existing bias mitigation methods trade accuracy for fairness (i.e., trade a reduction in accuracy for better fairness). In this paper, ...

Narayanan Nagarajan on LinkedIn: A technique to improve both ...

Narayanan Nagarajan's Post · A technique to improve both fairness and accuracy in artificial intelligence · More Relevant Posts · Design a machine learning system.

In-Processing Modeling Techniques for Machine Learning Fairness

Unlike the above measurements, overall accuracy equality emphasizes both true positive and true negative rates. This can be used in the scenarios where true ...

What methods can be used to improve prediction accuracy in ...

Transfer learning: To improve performance on a different related task, researchers might utilize a model that has already been trained on the first task as a ...

Enhancing Fairness and Performance in Machine Learning Models

Additionally, the trade-off between accuracy and fairness remains a fundamental tension in the field. To address these issues, we propose a bias ...

Improving fairness of artificial intelligence algorithms in Privileged ...

We start by suggesting a pre-process fairness mechanism, and two in-process mechanisms, based on supervised learning algorithms. To optimize ...

Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources ...

Moreover, mitigation approaches may introduce trade-offs between fairness and accuracy. For example, one approach to reducing algorithmic bias is to modify the ...

Improving Individual Fairness without Trading Accuracy

Then, an individual is treated by a machine learning model in an accurately fair way, if its prediction results for both the individual and the individual's ...

Predict Responsibly: Improving Fairness and Accuracy by Learning ...

In this work, we explore a simple version of this interaction with a two-stage framework containing an automated model and an external decision-maker. The model ...