Room P3.10, Mathematics Building

Cláudia Soares, ISR - Instituto de Sistemas e Robótica, Instituto Superior Técnico, Portugal
Distributed learning in large scale networks: from GPS-denied localization to MAP inference

Big Data can elicit greater insight, but storage or computational limitations — or even privacy concerns — challenge learning from massive data sets. The distributed paradigm fits such problems just right: such algorithms work on partial data and fuse intermediate results within local neighborhoods, over a distributed network of computing nodes. In this talk we will take a tour starting on GPS-denied localization and culminating on a general distributed MAP inference algorithm for graphical models.