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.
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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——
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