Abstract: A method of performing time series prediction by improper learning comprising calculating a plurality of filters based on a symmetric matrix and generating a mapping term based on a time series input and a function. The method may include comprising iteratively: transforming the function using the calculated plurality of filters; predicting an interim output using the transformed function and the mapping term; computing an error of the interim output based on a known output; and updating the mapping term based on the computed error. The method may include generating the mapping term through iterations over a predetermined interval and performing a time series prediction using the mapping term generated over the iterations.

Abstract: A method of performing time series prediction by improper learning comprising calculating a plurality of filters based on a symmetric matrix and generating a mapping term based on a time series input and a function. The method may include comprising iteratively: transforming the function using the calculated plurality of filters; predicting an interim output using the transformed function and the mapping term; computing an error of the interim output based on a known output; and updating the mapping term based on the computed error. The method may include generating the mapping term through iterations over a predetermined interval and performing a time series prediction using the mapping term generated over the iterations.