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 |