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

 

Abstract

 

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

 

 

22 במאי 2017, 15:00 
חדר 011, בניין כיתות-חשמל 
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