2 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This work examines how batch size, training duration, and estimator stabilization affect weight perturbation accuracy in fully connected MNIST networks, and identifies near-BP accuracy as a configuration- and budget-dependent possibility, rather than evidence of equal efficiency or an unconditional accuracy guarantee a...
Biologically motivated artificial visual learning requires local plasticity rules to be evaluated within architectures whose connectivity assumptions remain explicit. Convolutional Hebbian networks demonstrate that competitive local learning can support visual classification, but their performance is coupled to exa...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
