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Department of Mathematics,
Department of Mathematics,
University of California San Diego
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Math 278B: Mathematics of Information, Data, and Signals
Efstratios Tsoukanis
CGU
Active Learning Classification from a Signal Separation Perspective
Abstract:
In machine learning, classification is often approached as a function approximation problem. In this talk, we propose a active learning framework inspired by signal separation and super-resolution theory. Our approach enables efficient identification of class supports, even in the presence of overlapping distributions. This allows efficient clustering and label propagation from very few labeled points.
April 25, 2025
11:00 AM
APM 6402
Research Areas
Mathematics of Information, Data, and Signals****************************
