1. A method of determining a control signal for a robot, the method being performed by a special purpose computing platform having one or more processors executing instructions stored by a non-transitory computer-readable storage medium, the method comprising: receiving first input features of a first type and second input features of a second type; determining a subset of features by randomly selecting at least one of the first input features and at least one of the second input features; comparing individual features of the subset to corresponding features of a plurality of training feature sets, individual ones of the plurality of training feature sets comprising a number of training features, the number being equal to or greater than a quantity of features within the subset of features; based on the comparison, determining a similarity measure for a given training set of the plurality of training feature sets, the similarity measure characterizing a similarity between individual features of the subset and one or more features of the given training set; responsive to the similarity measure breaching a threshold, selecting one or more training sets from the plurality of training feature sets; determining one or more potential control signals for the robot, individual ones of the one or more potential control signals being associated with a corresponding training set of the plurality of training feature sets; and determining the control signal based on a transformation obtained from the one or more potential control signals; wherein: individual ones of the plurality of training feature sets comprise at least one feature of the first type and at least one feature of the second type; the individual ones of the plurality of training feature sets are obtained during a training operation of the robot, the training operation being performed responsive to receiving a training signal from the robot; and individual ones of the one or more potential control signals are determined based on the training signal and the one or more features of the given training set.