Patent ID: 8688616

Claim:
A method of analyzing data in high-dimensional space, comprising: (i) receiving, by a processor, observed data from a data source and at least one input model parameter set serving as a pre-determined solution candidate of a predefined problem, wherein the input model parameter set is related to the observed data via a prediction model; (ii) transforming, by the processor, the prediction model space associated with the input model parameter set into a reduced base, wherein the reduced base is associated with a set of coefficients that represents coordinates of any model parameter set in the reduced base, and the coefficients in the reduced base are fewer than model parameters in the input model parameter set; and (iii) sampling within the reduced base, by the processor, to generate a first output model parameter set in the reduced base, and reconstructing the first output model parameter set to generate a second output model parameter set in the prediction model space, wherein the second output model parameter set is compatible with the input model parameter set and fits the observed data, via the prediction model, within a predetermined threshold.