Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

This course is available on the MSc in Data Science, MSc in Geographic Data Science, MSc in Health Data Science, MSc in Operations Research & Analytics, MSc in Quantitative Methods for Risk Management ...

What Is Semi-Supervised Learning? Semi-supervised learning is a powerful machine learning technique that combines the strengths of supervised and unsupervised learning. It leverages a small amount of ...

Hao Yu (National University of Defense Technology), Chuan Ma (Chongqing University), Xinhang Wan (National University of Defense Technology), Jun Wang (National University of Defense Technology), Tao ...

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

Describe text classification and related terminology (e.g., supervised machine learning). Apply text classification to marketing data through a peer-graded project. Apply text classification to a ...