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Data compression and prediction are closely related. Thus prediction methods based on data compression algorithms have been suggested for the branch prediction problem. In this work we consider two universal compression algorithms: prediction by partial matching (PPM), and a recently developed method, context tree weighting (CTW). We describe the prediction algorithms induced by these methods. We also suggest adaptive algorithmsvariations of the basic methods that attempt to fit limited memorydoi:10.1145/279361.279370 fatcat:xgdlqlws25g7xm7q36nofwv56i