Hey guys,
I occasionally write articles on my blog, and I am happy to share the new one with you : https://bornlex.github.io/posts/differentiable-clustering/.
It came from something I was working for at work, and we ended up implementing something else because of the constraints that we have.
The method mixes different loss terms to achieve a differentiable clustering method that takes into account mutual info, semantic proximity and even constraints such as the developer enforcing two tags (could be documents) to be part of the same cluster.
Then it is possible to search the catalog using the clusters.
All of it comes from my mind, I used an AI to double check the sentences, spelling, so it might have rewritten a few sentences, but most of it is human made.
I've added the research flair even though it is not exactly research, but more experimental work.
Can't wait for your feedback !
Ju
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