- From: benjaminsavage via GitHub <sysbot+gh@w3.org>
- Date: Mon, 09 May 2022 17:24:04 +0000
- To: public-patcg@w3.org
A quote from that thread: > We believe that there are great benefits in aggregating reports from multiple source_site (or attribution_destination, depending on the use case) in a single request, to lower the overall level of noise. I agree. I would really like for IPA to support queries where the source_events span multiple source sites. I think this is a key use-case for ad-networks that show ads across the open web. We discuss this possible extension in our IPA proposal in the "[business privacy grain](https://docs.google.com/document/d/1KpdSKD8-Rn0bWPTu4UtK54ks0yv2j22pA5SrAD9av4s/edit#heading=h.3fuxnvaozwm4)" section. It's really hard though, and we haven't yet worked through all the issues with this. In particular, it requires careful design to ensure a malicious helper node cannot violate the "Vegas Rule". Reading through that thread, the use-case is really about training ML, not reporting. Rather than trying to get hundreds of independent breakdowns out of the API, it would probably be more efficient (from a DP perspective) to just train an ML model in MPC, and emit a trained model (with DP noise added). We allude to this as a possible future extension: [link](https://docs.google.com/document/d/1KpdSKD8-Rn0bWPTu4UtK54ks0yv2j22pA5SrAD9av4s/edit#heading=h.82taoxx5dmqm). This would have the added benefit of being able to model the interaction effects between these features. -- GitHub Notification of comment by benjaminsavage Please view or discuss this issue at https://github.com/patcg/private-measurement/issues/9#issuecomment-1121373245 using your GitHub account -- Sent via github-notify-ml as configured in https://github.com/w3c/github-notify-ml-config
Received on Monday, 9 May 2022 17:24:06 UTC