EE Seminar: Active Nearest-Neighbor Learning in Metric Spaces
(The talk will be given in English)
Speaker: Dr. Sivan Sabato
Department of Computer Science, Ben Gurion University
Monday, May 22nd, 2017
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
Active Nearest-Neighbor Learning in Metric Spaces
In this talk I address the challenges of active learning, an interactive machine learning paradigm that allows using data sources more effectively when data is expensive.
I will present an approach for active learning in general metric spaces, that does not require any input parameters, and obtains a competitive accuracy, compared to the accuracy of a non-interactive algorithm which gets all the data for free.
We prove that the proposed active algorithm can reduce the data costs significantly, and that this type of reduction cannot be achieved using simple subsampling.
Based on joint work with Aryeh Kontorovich and Ruth Urner