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

Claim 0:
1. A neural network training device for training a neural network for classifying objects, the neural network including a sequence of neural network layers, the device comprising:
a communication interface for accessing training data comprising object classifications;
a non-transitory neural network storage configured to store parameters for multiple layers of the sequence of neural network layers; and
a processor system configured to
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 and is configured to project 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.