Patent ID: 11875252
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 11:
12. A neural network training method for training a neural network, the neural network including a sequence of neural network layers, the method for classifying objects comprising:
accessing training data comprising object classifications;
storing parameters for multiple layers of the sequence of neural network layers; and
apply the sequence of neural network layers to data of the training data, and adjust the stored parameters to train the network, wherein
at least one layer of the sequence of neural network layers, both during training and in the trained neural network, is a projection layer, the projection layer being configured for a summing parameter applying the projection layer including projecting a layer input vector of the projection layer to a projection layer output vector in a limited multi label (LML) polytope which is a set of points in a unit hypercube with coordinates that sum to the summing parameter, the summing parameter being at least 2, the projecting including optimizing a layer loss-function applied to the projection layer output vector subject to the condition that the projection layer output vector sums to the summing parameter, wherein the layer loss-function includes a regulating term and a projection term, wherein optimizing the layer loss function includes applying an iterated approximation algorithm to obtain the projection layer output vector.