|
|
|
|
|
by inasio
344 days ago
|
|
Membership filters are very efficient filters that guarantee no false negatives, but false positives are possible (how much and how many can be adjusted based on the dataset and filter's parameters). An obvious application could something like checking whether passengers are in a no-fly list, where false-positives could be handled by further checks. As far as I know cuckoo filters [0] are the state of the art for this, but per this work in principle you could make very efficient with using a SAT (or XORSAT) solver that could generate many feasible solutions out of random SAT problems. - Google scholar pointed out this link to get a pdf for one of the papers cited in the repo [1] [0] https://en.wikipedia.org/wiki/Cuckoo_filter [1] http://t-news.cn/Floc2018/FLoC2018-pages/proceedings_paper_4... |
|
Why is this an obvious application? How does this application benefit from a "very efficient" first pass? Just the boarding process on an airplane takes 20-30 minutes; you can easily check the entire passenger manifest in an error-free way in much less time than that. People have to buy their tickets before the boarding process begins.