The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016) will be held in Heidelberg, Germany from Sep. 12-16.
The following oral presentation will be delivered.

Thanks to a number of researchers, RSSI-based localization accuracy has already reached a sufficient level.
However, it is still not easy-to-use technology because existing techniques need to collect enough RSSI data at each location.
We propose a technique to gather data efficiently by using machine learning techniques.
Our proposed algorithm is based on multi-task learning and Bayesian optimization.
This algorithm can remove the need to collect data of all location labels and select location labels to acquire new data efficiently.

—— presentation information ——
9/14(Wed) Indoor localisation (16:00~)
Efficient Calibration for RSSI-based Indoor Localization by Bayesian Experimental Design on Multi-task Classification
Masamichi Shimosaka, Osamu Saisho

—— Conference Information——
UbiComp 2016 Home
http://ubicomp.org/ubicomp2016/
UbiComp 2016 Program
http://ubicomp.org/ubicomp2016/program/program.php