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[D] Is it ill-advised to perform transfer learning with generalized linear models?

I’ve typically only performed transfer learning via fine-tuning with neural networks (eg. image classifiers from pre-trained MobileNet, etc.), but does the same idea hold for a model like logistic regression or CRF? I’d argue yes because your essentially just training a new model with non-randomized initial weights (a prior). But am I missing something?

I’m currently looking into cross-domain transfer learning for non-neural NER models, and I wanted to fine-tune the weights of a pre-trained CRF with some newly annotated user-generated data.

submitted by /u/Lewba
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.