Geometric Dataset Distances via Optimal Transport

7 Feb 2020David Alvarez-MelisNicolò Fusi

The notion of task similarity is at the core of various machine learning paradigms, such as domain adaptation and meta-learning. Current methods to quantify it are often heuristic, make strong assumptions on the label sets across the tasks, and many are architecture-dependent, relying on task-specific optimal parameters (e.g., require training a model on each dataset)... (read more)

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