Universal Information Processing

3 credits · Graduate

Universal schemes for information processing tasks such as compression, communication, sequential probability assignments, prediction, denoising, and filtering. Characterization of performance limits in stochastic, semi-stochastic, and individual sequence settings. Ziv-Lempel compression as an end goal, and as an engine for other information processing tasks. Trade Offs between performance (e.g. accuracy), amounts of data processed, and computation.