4 ms·

We have gradient free algorithms: Hebbian learning. Since 1949?

• uoaei 2y ago
  And there's good reasons why we use gradients today.
• sva_ 2y ago
  That's more a theory/principle, not an algorithm by itself.
  • erikerikson 2y ago
    It is an update rule: Wij = f(Wij, xi, xj) The weight of the connection between nodes i and j is modified by a function over the activations or inputs of node i and j. The are many variants of back propagation too. Regardless, yes it would be used within a network model such as a Hopfield network.
  • erikerikson 2y ago
    See also https://en.m.wikipedia.org/w/index.php?title=Generalized_Hebbian_algorithm&wprov=rarw1 https://en.m.wikipedia.org/w/index.php?title=Generalized_Heb...