Options for single-pass and single-shot learning mechanisms


As well as being a notable feature of biological learning mechanisms and therefore worthy of study in its own right, single-shot and single-pass learning offers many advantages including (potentially huge) gains in speed and energy use, as well as continuous and adaptive learning.  I would like to explore the options primarily in the context of - but not limited to - neuromorphic hardware and neurally-inspired learning and inference algorithms.

It may be useful to describe relevant aspects of the recently published BitBrain algorithm as one example.

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Day Time Location
Tue, 02.05.2023 14:00 - 15:00 Sala panorama
Mon, 08.05.2023 16:00 - 17:00 Lecture room
Fri, 05.05.2023 14:00 - 15:00 Lecture room


Michael Hopkins


Maxime Fabre
Luca Fehlings
Gaurvi Goyal
Michael Hopkins
Melika Payvand