G2L: A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning

no code implementations • 7 Jul 2022 • John R. Kender, Bishwaranjan Bhattacharjee, Parijat Dube, Brian Belgodere

Transfer learning is a deep-learning technique that ameliorates the problem of learning when human-annotated labels are expensive and limited.

Transfer Learning

P2L: Predicting Transfer Learning for Images and Semantic Relations

no code implementations • 20 Aug 2019 • Bishwaranjan Bhattacharjee, John R. Kender, Matthew Hill, Parijat Dube, Siyu Huo, Michael R. Glass, Brian Belgodere, Sharath Pankanti, Noel Codella, Patrick Watson

We use this measure, which we call "Predict To Learn" ("P2L"), in the two very different domains of images and semantic relations, where it predicts, from a set of "source" models, the one model most likely to produce effective transfer for training a given "target" model.

Transfer Learning