# Mimir at CIDR, EDBT

Some great news for the Mimir project. After picking up a massive \$2.7m grant this summer (in collaboration with NYU and IIT) to build an interactive data curation system, we just got notified of two new paper accepts.

Inference in graphical models requires a lot of hand tuning. Approximation algorithms are fast, but imprecise. Exact algorithms work well, until they don't. In this paper, Ying Yang described a new Leaky Join'' operator that allows for convergent-online inference. In short, a query plan consisting of leaky join operators behaves like an online algorithm in that it produces (high quality) approximations prior to completion. However, unlike classical online algorithms, it is guaranteed to converge with only minimal overhead compared to a standard classical join.