Patent ID: 11915152
Assignee: D5AI LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A machine learning (ML) computer system for training a student ML system iteratively through machine learning on training data to perform a machine learning task, wherein:
the student ML system comprises an input layer, an output layer, and at least a first inner layer between the input and output layers;
each layer comprises at least one node, such that the first inner layer comprises at least a first node;
the first node of the first inner layer outputs an activation value for each set of input values to the first node of the first inner layer;
the activation value is determined based on an activation function for the first node of the first inner layer and based on learned parameters for the first node of the first inner layer; and
following iterations of the training of the student ML system, the learned parameters for the first node of the first inner layer are updated,
wherein the machine learning computer system comprises:
a learning coach ML system that is in communication with the student ML system, wherein the learning coach ML system has been trained through machine learning to determine one or more revised hyperparameter values for the student ML system, wherein each of the one or more revised hyperparameter values controls an aspect of the machine learning by the student ML system, and wherein the learning coach ML system comprises an input layer and an output layer, and wherein the learning coach ML system determines the one or more revised hyperparameter values for the student ML system based on input to the learning coach ML system from the student ML system, wherein the input to the learning coach ML system from the student ML system is input to the input layer of the learning coach ML system, and wherein the input from the student ML system comprises observations about an internal state of the student ML system during training of the student ML system, wherein the observations about the internal state of the student ML system comprise values related to the learned parameters for the first node on the first inner layer of the student ML system and the activation values for the first node on the first inner layer of the student ML system; and
a reference system for generating a set of additional training data for the student ML system, wherein the reference system comprises a ML system, wherein the additional training data generated by the reference system are input to the input layer of the student ML system, and wherein the learning coach ML system has been trained, through machine learning, to determine the one or more revised hyperparameter values for the student ML system that is implemented by the student ML system based on the observations about the first node on the first inner layer of the student ML system from a training of the student ML system with the set of additional training data generated by the reference system.