Almost everywhere high nonuniform complexity
Journal of Computer and System Sciences
Completeness and weak completeness under polynomial-size circuits
Information and Computation
MAX3SAT is exponentially hard to approximate if NP has positive dimension
Theoretical Computer Science
COCO '98 Proceedings of the Thirteenth Annual IEEE Conference on Computational Complexity
Dimension in Complexity Classes
COCO '00 Proceedings of the 15th Annual IEEE Conference on Computational Complexity
Hausdorff Dimension in Exponential Time
CCC '01 Proceedings of the 16th Annual Conference on Computational Complexity
Note: fractal dimension and logarithmic loss unpredictability
Theoretical Computer Science
The dimensions of individual strings and sequences
Information and Computation
Journal of Computer and System Sciences - Special issue on COLT 2002
SIGACT news complexity theory column 48
ACM SIGACT News
Hausdorff dimension and oracle constructions
Theoretical Computer Science
Dimension, entropy rates, and compression
Journal of Computer and System Sciences
A note on dimensions of polynomial size circuits
Theoretical Computer Science
Theoretical Computer Science
Online learning and resource-bounded dimension: winnow yields new lower bounds for hard sets
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Two open problems on effective dimension
CiE'06 Proceedings of the Second conference on Computability in Europe: logical Approaches to Computational Barriers
Hardness hypotheses, derandomization, and circuit complexity
FSTTCS'04 Proceedings of the 24th international conference on Foundations of Software Technology and Theoretical Computer Science
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Resource-bounded dimension is a complexity-theoretic extension of classical Hausdorff dimension introduced by Lutz (in: Proceedings of the 15th Annual IEEE Conference on Computational Complexity, 2000, pp. 158-169) in order to investigate the fractal structure of sets that have resource-bounded measure 0. For example, while it has long been known that the Boolean circuit-size complexity class SIZE(α2n/n) has measure 0 in ESPACE for all 0≤α≤1, we now know that SIZE(α2n/n) has dimension α in ESPACE for all 0≤α≤1. The present paper furthers this program by developing a natural hierarchy of "rescaled" resource-bounded dimensions. For each integer i and each set X of decision problems, we define the ith-order dimension of X in suitable complexity classes. The zeroth-order dimension is precisely the dimension of Hausdorff (Math. Ann. 79 (1919) 157-179) and Lutz (2000). Higher and lower orders are useful for various sets X. For example, we prove the following for 0≤α≤1 and any polynomial q(n)≥n2: 1. The class SIZE(2αn) and the time- and space-bounded Kolmogorov complexity classes KTq(2αn) and Ksq(2αn) have first-order dimension α in ESPACE. 2. The classes SIZE(2nα), KTq(2nα), and KSq(2nα) have second-order dimension α in ESPACE. 3. The classes KTq(2n(1-2-αn)) and KSq(2n(1-2αn) have negative-first-order dimension α in ESPACE.