Let X be an infinite sequence of 0’s and 1’s. Let f be a computable function. Recall that X is strongly f-random if and only if the a priori Kolmogorov complexity of each finite initial segment τ of X is bounded below by f(τ) minus a constant. We study the problem of finding a PA-complete Turing oracle which preserves the strong f-randomness of X while avoiding a Turing cone. In the context of this problem, we prove that the cones which cannot always be avoided are precisely the K-trivial ones. We also prove: (1) If f is convex and X is strongly f-random and Y is Martin-Löf random relative to X, then X is strongly f-random relative to Y. (2) X is complex relative to some oracle if and only if X is random with respect to some continuous pro...
We study the power of randomized polynomial-time non-adaptive reductions to the problem of approxima...
In this dissertation we consider two different notions of randomness and their applications to probl...
We compare various notions of algorithmic randomness. First we consider relativized randomness. A s...
Let f be a computable function from finite sequences of 0's and 1's to real numbers. We prove that s...
An infinite binary sequence X is Kolmogorov-Loveland (or KL) random if there is no computable non-mo...
Abstract. Schnorr famously proved that Martin-Löf-randomness of a sequence A can be characterised v...
Schnorr famously proved that Martin-Löf-randomness of a sequence A can be characterised via the co...
This paper defines a new notion of bounded computable randomness for certainclasses of sub-computabl...
Let R be a notion of algorithmic randomness for individual subsets of N. We say B is a base for R ra...
We establish the truth of the "instance complexity conjecture" in the case of DEXT-complet...
In this dissertation we consider two different notions of randomness and their applica-tions to prob...
Abstract. In the theory of algorithmic randomness, several notions of random sequence are defined vi...
Abstract. Every K-trivial set is computable from an incomplete Martin-Löf random set, i.e., a Marti...
Abstract. Every K-trivial set is computable from an incomplete Martin-Löf random set, i.e., a Marti...
Kolmogorov has defined the conditional complexity of an object y when the object x is already given ...
We study the power of randomized polynomial-time non-adaptive reductions to the problem of approxima...
In this dissertation we consider two different notions of randomness and their applications to probl...
We compare various notions of algorithmic randomness. First we consider relativized randomness. A s...
Let f be a computable function from finite sequences of 0's and 1's to real numbers. We prove that s...
An infinite binary sequence X is Kolmogorov-Loveland (or KL) random if there is no computable non-mo...
Abstract. Schnorr famously proved that Martin-Löf-randomness of a sequence A can be characterised v...
Schnorr famously proved that Martin-Löf-randomness of a sequence A can be characterised via the co...
This paper defines a new notion of bounded computable randomness for certainclasses of sub-computabl...
Let R be a notion of algorithmic randomness for individual subsets of N. We say B is a base for R ra...
We establish the truth of the "instance complexity conjecture" in the case of DEXT-complet...
In this dissertation we consider two different notions of randomness and their applica-tions to prob...
Abstract. In the theory of algorithmic randomness, several notions of random sequence are defined vi...
Abstract. Every K-trivial set is computable from an incomplete Martin-Löf random set, i.e., a Marti...
Abstract. Every K-trivial set is computable from an incomplete Martin-Löf random set, i.e., a Marti...
Kolmogorov has defined the conditional complexity of an object y when the object x is already given ...
We study the power of randomized polynomial-time non-adaptive reductions to the problem of approxima...
In this dissertation we consider two different notions of randomness and their applications to probl...
We compare various notions of algorithmic randomness. First we consider relativized randomness. A s...