References for: assertion
Full identifier: https://w3id.org/np/RAFarA0bwpHsznbcw3wXi4Za4Bzu9KtsPOK-fFk1yOCLg#assertion
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links a nanopublication to its assertion
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links a nanopublication to its provenance
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links a nanopublication to its assertion
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You can not run a closed model yourself, right? well...
They prevent information leakage through quantum light properties
What?!
Simply:you can compute the network outputs but not recreate the weights and the API cannot access your data!
@RLEatMIT
@KfirSulimany @Dirk_Englund https://twitter.com/LChoshen/status/1823374595334009145/photo/1
The basic Idea is that for every multiplication in the network you multiply two symmetric things an input and an output matrix.
So, if each side can send a matrix but only read the output each can keep their secret (one the input one the model weights)
https://www.alphaxiv.org/abs/2408.05629
And apparently you can multiply (super fast) by encoding the matrix as a light wave, then the multiplication is the two waves meeting and the output is more or less the only thing you can do.
I was involved in the "more or less", e.g. to avoid reconstruction through a canonical basis as inputs you can use invariances such as sending a permuted network each time
https://www.alphaxiv.org/abs/2408.05629
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links a nanopublication to its assertion
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machinelearning
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privacy
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quantum-securemultipartydeeplearning
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links a nanopublication to its assertion
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quantumcomputing
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links a nanopublication to its assertion
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securemultipartycomputation
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links a nanopublication to its assertion
http://www.nanopub.org/nschema#hasAssertion
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links a nanopublication to its provenance
http://www.nanopub.org/nschema#hasProvenance
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links a nanopublication to its provenance
http://www.nanopub.org/nschema#hasProvenance
provenance
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assertion
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2024-09-03T21:16:02.887Z
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links a nanopublication to its provenance
http://www.nanopub.org/nschema#hasProvenance
provenance
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assertion
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2024-09-03T21:16:02.887Z
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