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Switchable Representation Learning Framework with Self-compatibility. (arXiv:2206.08289v1 [cs.AI])
cs.LG updates on arXiv.org arxiv.org
Real-world visual search systems involve deployments on multiple platforms
with different computing and storage resources. Deploying a unified model that
suits the minimal-constrain platforms leads to limited accuracy. It is expected
to deploy models with different capacities adapting to the resource
constraints, which requires features extracted by these models to be aligned in
the metric space. The method to achieve feature alignments is called
"compatible learning". Existing research mainly focuses on the one-to-one
compatible paradigm, which is limited in learning …
ai arxiv framework learning representation representation learning