mccormick.northwestern.edu

Exploring the Connections Among Machine Learning, Interpretability, and Logic

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...
Forbes

Explainable AI: The Importance Of Adding Interpretability Into Machine Learning

Dr. Adi Hod. Cofounder & CEO at Velotix. Driven by a passion for data and cybernetic AI. Entrepreneur, professor, leader & innovator. AI is fast becoming embedded in industries, economies and lives, ...
EurekAlert!

Tensor networks: Enhancing interpretability and efficiency in quantum-inspired machine learning

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...
insideHPC

Machine Learning Interpretability with Driverless AI

Data visualization techniques for representing high-degree interactions and nuanced data structures. Contemporary linear model variants that incorporate machine learning and are appropriate for use in ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly ...
Microsoft

Microsoft responsible machine learning capabilities build trust in AI systems, developers say

Anyone who runs a business knows that one of the hardest things to do is accuse a customer of malfeasance. That’s why, before members of Scandinavian Airlines’ (SAS) fraud detection unit accuse a ...