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[D] How do you combine two learned models trained on partitioned data of the same distribution, to a single model?

If we have a single large dataset D, and partitioned into A and B and put on devices.

I make two replicas of M1 and M2 from a same model M and also with same initial weights(same seed). I put these on the above two devices and train them separately.

How do I combine(if it’s the word) these two models’ experience into a single one(like a model which has learned the entire data D)?

submitted by /u/MasterInternet
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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.