Journal of Computer and System Sciences - Special issue on COLT 2002
Model selection by sequentially normalized least squares
Journal of Multivariate Analysis
Predictability of individuals' mobility with high-resolution positioning data
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Predictive complexity and generalized entropy rate of stationary ergodic processes
ALT'12 Proceedings of the 23rd international conference on Algorithmic Learning Theory
Online portfolio selection: A survey
ACM Computing Surveys (CSUR)
Similarity in languages and programs
Theoretical Computer Science
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The problem of predicting the next outcome of an individual binary sequence using finite memory is considered. The finite-state predictability of an infinite sequence is defined as the minimum fraction of prediction errors that can be made by any finite-state (FS) predictor. It is proven that this FS predictability can be achieved by universal sequential prediction schemes. An efficient prediction procedure based on the incremental parsing procedure of the Lempel-Ziv data compression algorithm is shown to achieve asymptotically the FS predictability. Some relations between compressibility and predictability are discussed, and the predictability is proposed as an additional measure of the complexity of a sequence