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.
Go to group wiki Go to wiki users Info
|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|