In March, Tom Loveless, a fellow at the Brookings Institution, took an outdated swipe at the logic behind moving toward a student-centered learning system. He in essence suggested that because the ...

Arguably, the problem of learning represents a gateway to understanding intelligence in brains and machines, to discovering how the human brain works and to making intelligent machines that learn from ...

As a data scientist, I have a handful of books that serve as important resources for my work in the field – “Statistical Learning with Sparsity – The Lasso and Generalizations” by Trevor Hastie, ...

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 ...

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...