Apparently, wrong: we got THREE of these. Clear reject, with high confidence. I couldn't bring myself to read the reviews for a week.I can't describe how crushing this rejection was. (Spring 2023) 10/n
@thegautamkamath
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Publishing Non-Technical ML Research: Venue Selection Challenges
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Even worse, it wasn't clear what to do with this paper. There are few venues in ML that accept non-technical or opinion pieces. We thought it was a shoo-in for Venue 1, and didn't have a backup plan. 8/n
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Peer Review Frustration: Vague Stylistic Critique in Major Revision
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This was *incredibly* frustrating. Usually major revisions feature specific and technical critiques. It was rejected for a vague and stylistic critique. This is the closest I've come to emailing a PC chair in frustration, but I held my tongue (it's not their fault). 7/n
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Academic Paper Rejection: Vague Revision Requests Frustrate Researchers
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We were given a major revision. Requested changes were vague: "tighten" the writing. Clarify differences with prior work. Make points clearer. I honestly thought it was fine before on all counts, but OK, we honestly tried more. Nope. Not good enough, reject. (late 2022) 6/n
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Public Data for Private ML: Differential Privacy Research Agenda
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Personally, I have been super interested in public data for private ML. I honestly think this is the future of DP deployments. So this paper felt *super* core to my entire research agenda: how exactly we think we, as a field, should push forward. 4/n
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Critical Position Paper Submitted to Topical Conference
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Florian had some convos with others on this topic, including Nicholas. We saw a topical conference with a call for position papers. We decided to write and submit a critical piece (self-critical of some of our previous works as well!) 3/n
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Privacy Challenges in Public Data for Machine Learning
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This work started through some conversations with Florian (Summer 2022). We noticed that while public data was *really* helpful in private ML, weird things happened. An arms race of larger "public" datasets. Evaluating on datasets that didn't have much to do with privacy. Etc 2/n
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Differential Privacy in Large-Scale AI Pretraining Wins ICML Award
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"Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining," with @florian_tramer & Nicholas Carlini got an #ICML2024 best paper award! https://
x.com/thegautamkamat
h/status/1603383883126669312
… : the personal side of this research, emotional high & lows, & more 1/n -
Differential Privacy Foundations Published in Journal
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Note that the original paper that introduced differential privacy was also published in JPC: https://
journalprivacyconfidentiality.org/index.php/jpc/
article/view/405
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Research Paper Journey: From arXiv to NeurIPS to Peer Review
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We originally planned this paper as a cute note to live on arXiv. But people seemed interested, so we thought why not submit it to #NeurIPS2020. When we found out that the @uscensusbureau was going to use it, it needed a proper peer review. The only journal we considered was JPC.