In the new paper Learning in High Dimension Always Amounts to Extrapolation, a team from Facebook AI Research and New York University that includes Yann LeCun theoretically and empirically challenges ...

The model may turn out to be far too complex if we continuously keep adding more variables. Will fail to simplify as it is memorizing the training data. We say Model is over-fitting when the accuracy ...

Data-driven materials science has realized a new paradigm by integrating materials domain knowledge and machine-learning (ML) techniques. However, ML-based research has often overlooked the inherent ...