Enron
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Layered Ego Networks in Email Communication: From Enron to the Jmail Archive
Announce Type: new Abstract: Email archives offer a rare view of social relationships through repeated communication, but it remains unclear how well classical ego network layering applies to digital interaction data. This paper compares two public email archives with sharply contrasting structures: Enron, a workplace corpus involving around 150 users, and Jmail, a single-ego archive centered on an exceptionally active focal actor whose communication volume is more than twenty times higher...
Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption
arXiv:2606.03191v2 Announce Type: replace Abstract: Many NLP or recommendation models begin by mapping discrete client inputs to embedding vectors. Since inputs can reveal sensitive information, the embedding step must be protected in privacy-preserving inference. Fully Homomorphic Encryption (FHE) enables inference over encrypted client data, but turns embedding lookup from simple table access into homomorphic computation.
Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption
arXiv:2606.03191v1 Announce Type: new Abstract: Many NLP or recommendation models begin by mapping discrete client inputs to embedding vectors. Since inputs can reveal sensitive information, the embedding step must be protected in privacy-preserving inference. Fully Homomorphic Encryption (FHE) enables inference over encrypted client data, but turns embedding lookup from simple table access into homomorphic computation.
Does JD Vance have to choose between Pope Leo and Peter Thiel?
Pope Leo XIV has chosen a side in the AI battle gripping Washington: He’s Team Anthropic. No, Leo isn’t weighing in on the Trump administration’s ongoing battle with the frontier AI lab and no, he isn’t donating to its super PAC of choice. But on Monday when he unveiled Magnifica Humanitas, his first encyclical letter, on “safeguarding the human person in the time of artificial intelligence,” it was hard to miss that Anthropic co-founder Christopher Olah was there at the...
Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption
Announce Type: replace Abstract: Many NLP or recommendation models begin by mapping discrete client inputs to embedding vectors. Since inputs can reveal sensitive information, the embedding step must be protected in privacy-preserving inference. Fully Homomorphic Encryption (FHE) enables inference over encrypted client data, but turns embedding lookup from simple table access into homomorphic computation.