TY  - CONF
AU  - Lohoff, Jamie
AU  - Neftci, Emre
TI  - Finding new bio-plausible Learning Rules using Deep Reinforcement Learning
PB  - RWTH Aachen
M1  - FZJ-2024-01020
PY  - 2023
AB  - Gradient-based learning is still the best bet when training spiking neural networks on supervised tasks. Although backpropagation, the state-of-the-art in modern AI, is not bio-plausible, there exists a wide range of approximations with this property that achieve competitive performance, e.g. e-prop[1,2]. We propose a new framework called AlphaGrad that could find more such learning rules by systematically exploring the search space using Deep Reinforcement Learning and methods from Automatic Differentiation(AD).
T2  - nternational conference on neuromorphic, natural and physical computing
CY  - 25 Oct 2023 - 27 Oct 2023, Hanover (Germany)
Y2  - 25 Oct 2023 - 27 Oct 2023
M2  - Hanover, Germany
LB  - PUB:(DE-HGF)24
DO  - DOI:10.34734/FZJ-2024-01020
UR  - https://juser.fz-juelich.de/record/1021872
ER  -