US 2021/0174265 A1 · BUILDING DEEP LEARNING ENSEMBLES WITH DIVERSE TARGETS

Abstract

A computer-implemented method of training an ensemble machine learning system comprising a plurality of ensemble members. The method includes selecting a shared objective and an objective for each of the ensemble members. The method further includes training each of the ensemble members according to each objective on a training data set, connecting an output of each of the ensemble members to a joint optimization machine learning system to form a consolidated machine learning system, and training the consolidated machine learning system according to the shared objective and the objective for each of the ensemble members on the training data set. The ensemble members can be the same or different types of machine learning systems. Further, the joint optimization machine learning system can be the same or a different type of machine learning system than the ensemble members.

Claims30

Dependent claims

A computer-implemented method of training an ensemble machine learning system comprising a plurality of ensemble members, the method comprising:

training, by a computer system, individually the plurality of ensemble members on a training data set, wherein each of the plurality of ensemble members is training according to an associated objective for the ensemble member;
and
after training the plurality of ensemble members, training, by the computer system, a consolidated machine learning system, wherein:
the consolidated machine learning system comprises the plurality of ensemble members and a joint optimization machine learning system, such that an output from each of the plurality of ensemble members is input to the joint optimization machine learning system;
the joint optimization machine learning system is training according to a shared objective;
and
each of the plurality of ensemble members is training according to both the shared objective and the associated objective for the plurality of ensemble members.

4 more elements

A computer system for training an ensemble machine learning system comprising a plurality of ensemble members, the computer system comprising:

a processor;
and
a memory coupled to the processor, the memory storing:
the plurality of ensemble members;
a joint optimization machine learning system;
and
instructions that, when executed by the processor, cause the computer system to:
train individually the plurality of ensemble members on a training data set, wherein each of the plurality of ensemble members is training according to an associated objective for the ensemble member;
and
after training the plurality of ensemble members, train a consolidated machine learning system, wherein:
the consolidated machine learning system comprises the plurality of ensemble members and the joint optimization machine learning system, such that an output from each of the plurality of ensemble members is input to the joint optimization machine learning system;
the joint optimization machine learning system is training according to a shared objective;
and
each of the plurality of ensemble members is training according to both the shared objective and the associated objective for the plurality of ensemble members.

11 more elements

Dependencies are inferred from the claim text.

Building deep learning ensembles with diverse targets

Life of this patent

Building deep learning ensembles with diverse targets

Life of this patent

Abstract

Claims30