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BitBrain and other methods for single-pass and continuous learning

Many contemporary machine learning/AI methods require extensive computation for training which consumes a great deal of time and energy resource. Their inference mechanism also tends to have a large energy-latency product. We will discuss methods that can learn in a single-pass. This usually also promotes an ability to learn continuously and, if necessary, forget earlier information if it is considered that the problem is changing over time.

It might be a good idea for participants to watch the NICE 2022 video as some background to BitBrain so that we can start with a shared basic foundation for the ideas:

https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=235&publicVideoID=8944.

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Timetable

Day Time Location
Wed, 04.05.2022 14:00 - 15:00 Lecture room
Mon, 09.05.2022 15:00 - 16:00 Lecture room

Moderator

Michael Hopkins

Members

Matteo Cartiglia
Jakub Fil
Michael Hopkins
Joscha Ilmberger
Edward Jones
Willian Soares girao
Simon Thorpe