Polymorphic pruning of neural networks

A pruning system comprising:

• a memory;
• and
• a processor that is configured to execute machine readable instructions stored in the memory for causing the processor to:
• receive an input dataset;
• upon providing the input dataset to a training process of a machine learning model, determine information about weights associated with the machine learning model;
• determine an objective function using the information about the weights associated with the machine learning model;
• determine a solution vector to the objective function;
• determine a pruning mask from the solution vector;
• and
• update the machine learning model using the pruning mask and the solution vector.

A non-transitory computer-readable storage medium storing a plurality of instructions executable by a processor, the plurality of instructions when executed by the processor cause the processor to perform operations comprising:

• receiving an input dataset;
• upon providing the input dataset to a training process of a machine learning model, determining information about weights associated with the machine learning model;
• determining an objective function using the information about the weights associated with the machine learning model;
• determining a solution vector to the objective function;
• determining a pruning mask from the solution vector;
• and
• updating the machine learning model using the pruning mask and the solution vector.