1. A computer-implemented method comprising: receiving, at a processor, an input signal from a sensor; predicting a plurality of filters using a trained machine learning system, the trained machine learning system comprising a random decision forest having individual filters stored at leaf nodes of trees of the random decision forest, individual ones of the filters being associated with individual elements of the signal and conditioned on local appearances of the signal associated with the individual elements; computing a filtered version of the input signal by applying, using the processor, the individual ones of the filters to the associated individual elements of the signal.