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Duality Principle and Biologically Plausible Learning: Connecting the Representer Theorem and Hebbian Learning.

, , and . CoRR, (2023)

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Duality Principle and Biologically Plausible Learning: Connecting the Representer Theorem and Hebbian Learning., , and . CoRR, (2023)A biologically plausible neural network for local supervision in cortical microcircuits., , , , and . CoRR, (2020)A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit., , and . CoRR, (2021)Exploration and extension of the similarity matching framework: feature learning, nonlinear methods and transformation learning.. Loughborough University, UK, (2020)British Library, EThOS.A normative framework for deriving neural networks with multi-compartmental neurons and non-Hebbian plasticity., , , , and . CoRR, (2023)Neural Networks for Efficient Nonlinear Online Clustering., , and . ICONIP (1), volume 10634 of Lecture Notes in Computer Science, page 316-324. Springer, (2017)Unlocking the Potential of Similarity Matching: Scalability, Supervision and Pre-training., , , , and . CoRR, (2023)Interpretable Image Clustering via Diffeomorphism-Aware K-Means., , , , , and . CoRR, (2020)Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy., , , , and . NeurIPS, (2022)Online Representation Learning with Single and Multi-layer Hebbian Networks for Image Classification., and . ICANN (1), volume 10613 of Lecture Notes in Computer Science, page 354-363. Springer, (2017)