Fractal dimension and logarithmic loss unpredictability.

DOI10.1016/S0304-3975(03)00138-5zbMath1053.68053MaRDI QIDQ1401414

John M. Hitchcock

Publication date: 17 August 2003

Published in: Theoretical Computer Science (Search for Journal in Brave)

zbMATH Keywords

Hausdorff dimension

Mathematics Subject Classification ID

Algorithmic information theory (Kolmogorov complexity, etc.) (68Q30)

Related Items

Scaled dimension and nonuniform complexity ⋮ Hausdorff dimension and oracle constructions ⋮ Dimensions of Copeland-Erdös sequences ⋮ Effective Dimensions and Relative Frequencies ⋮ Fractal property of generalized M-set with rational number exponent ⋮ Dimension is compression ⋮ Base invariance of feasible dimension ⋮ Effective dimensions and relative frequencies ⋮ Finite-state dimension and real arithmetic ⋮ Generalised entropies and asymptotic complexities of languages ⋮ Polylog space compression, pushdown compression, and Lempel-Ziv are incomparable ⋮ Complex network dimension and path counts ⋮ Dimension, entropy rates, and compression ⋮ Prediction and dimension ⋮ Pushdown dimension ⋮ Modelling fractal patterns via the qualitative equivalence of a nonlinear ODE ⋮ Scaled dimension and the Kolmogorov complexity of Turing-hard sets ⋮ Dimension extractors and optimal decompression ⋮ Distance computation of ontology vector for ontology similarity measuring and ontology mapping ⋮ Entropy rates and finite-state dimension

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Algorithmic approach to the prediction problem
• The complexity and effectiveness of prediction algorithms
• A tight upper bound on Kolmogorov complexity and uniformly optimal prediction
• Endliche Automaten und Zufallsfolgen
• Universal prediction of individual sequences
• Dimension in Complexity Classes
• Universal prediction