Tag: IBM

AI Machine Learning & Data Science Research

IBM’s Type Prediction Systems Eliminate Need for Manual Annotations on Knowledge Graphs

A research team from IBM introduces two systems for predicting information type: The TypeSuggest module, an unsupervised system designed to generate types for a set of seed query terms input by the user; and an Answer Type prediction module for predicting the correct answer type for user-provided questions.

AI Machine Learning & Data Science Research

Improving ML Fairness: IBM, UMich & ShanghaiTech Papers Focus on Statistical Inference and Gradient-Boosting

A team from University of Michigan, MIT-IBM Watson AI Lab and ShanghaiTech University publishes two papers on individual fairness for ML models, introducing a scale-free and interpretable statistically principled approach for assessing individual fairness and a method for enforcing individual fairness in gradient boosting suitable for non-smooth ML models.