- Auditing and Enforcing Conditional Fairness via Optimal Transport🔍
- Improving Fairness in Criminal Justice Algorithmic Risk ...🔍
- Fairness & Robustness in Machine Learning🔍
- An Algorithmic Foundation for Fair🔍
- Fairness Explainability using Optimal Transport with Applications in ...🔍
- Optimal Transport in Data Science🔍
- When Fair Classification Meets Noisy Protected Attributes🔍
- Measuring Bias with Wasserstein Distance🔍
Optimal Transport for Fairness
Auditing and Enforcing Conditional Fairness via Optimal Transport
When model outputs are continuous, our methods target full equality of the conditional distributions, unlike other methods that only consider ...
Improving Fairness in Criminal Justice Algorithmic Risk ... - DeepAI
We combine a machine learning classifier trained in a novel manner with an optimal transport adjustment for the relevant joint probability ...
Fairness & Robustness in Machine Learning
Fairness & Robustness in Machine Learning · Using optimal transport Theory (with E. del Barrio (U. Valladolid), P. · Fairness in clustering and allocation ...
An Algorithmic Foundation for Fair, Secure, and Differentially Private ...
Optimal transport (OT) is a framework that can be used to facilitate the optimal allocation of resources in a network with multiple source and target nodes. To ...
Fairness Explainability using Optimal Transport with Applications in ...
This article discusses the importance of fairness and explainability in Artificial Intelligence systems and proposes a comprehensive ...
Optimal Transport in Data Science - ICERM - Brown University
The proposed method incorporates relational or functional profiles of neighboring variables along multiple common neighbors, which are fitted with Gaussian ...
When Fair Classification Meets Noisy Protected Attributes
de-noised constraints that allow for near optimal fairness [13], or a ... In Optimal transport. Springer,. 93–111. [60] Serena Wang, Wenshuo Guo ...
Measuring Bias with Wasserstein Distance
We broadly describe fairness as a probability distribution over outcomes, and use optimal transport to study the difference between an observed distribution of ...
A Statistical Test for Probabilistic Fairness - NSF PAR
In this pa- per, we use ideas from the theory of optimal transport to propose a statistical hypothesis test for detecting unfair classifiers. Leveraging the ...
Transport-based Counterfactual Models
More specifically, we argue that optimal-transport theory defines relevant transport-based counterfactual models, as they are numerically feasible ...
Optimal transport for machine learning - Gabriel Peyre, Ecole ...
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” ...
FlipTest: Fairness Testing via Optimal Transport | Papers With Code
FlipTest: Fairness Testing via Optimal Transport ... We present FlipTest, a black-box technique for uncovering discrimination in classifiers.
Fairness and discrimination, PhD Course, #4 Wasserstein Distances ...
This article discusses the concept of Wasserstein distance and optimal transport in the context of fairness and discrimination. The Cramér ...
Marco Cuturi - A primer on Optimal Transport Theory and Algorithms
A primer on Optimal Transport Theory and Algorithms, with Applications to Single-Cell Omics by Marco Cuturi (Apple ML Research & CREST ...
optimal transport; theoretical issues in deep learning; societal ... societal considerations of representation learning including fairness, safety, privacy, and ...
Statistical and Computational Aspect of Sliced Optimal Transport
Abstract: As machine learning/inference tasks boil down to comparing or transforming complicated probability distributions, optimal ...
What's current status of Optimal Transportation? : r/math - Reddit
In applied mathematics, optimal transport theory is enormously popular and trendy right now. The main figures include Gabriel Peyre, Marco ...
"Optimal Transport for Statistics and Machine Learning ... - YouTube
Abstract Since its introduction more than two centuries ago, optimal transport has flourished into a rich mathematical field allowing us to ...
Practical Individual Fairness Algorithms - YouTube
research interests are Model fusion and federated learning; Algorithmic fairness; Applications of optimal transport in machine learning ...
Blockchain-based energy consumption approaches in IoT - Nature
... transport control, e-commerce systems etc. IoT devices, ranging from ... The optimal learning design, on the other hand, could achieve ...