English
Related papers

Related papers: Derandomizing from Random Strings

200 papers

This paper is motivated by a conjecture that BPP can be characterized in terms of polynomial-time nonadaptive reductions to the set of Kolmogorov-random strings. In this paper we show that an approach laid out in [Allender et al] to settle…

Computational Complexity · Computer Science 2015-07-01 Eric Allender , Harry Buhrman , Luke Friedman , Bruno Loff

The coding theorem for Kolmogorov complexity states that any string sampled from a computable distribution has a description length close to its information content. A coding theorem for resource-bounded Kolmogorov complexity is the key to…

Computational Complexity · Computer Science 2024-09-20 Shuichi Hirahara , Zhenjian Lu , Mikito Nanashima

Discrete probabilistic programs (DPPs) provide a highly expressive formalism for compactly defining arbitrary finite probabilistic models. This expressivity comes at a price: DPP inference is PSPACE-hard. In this work, we show that DPP…

Data Structures and Algorithms · Computer Science 2026-04-29 Benedikt Peterseim , Milan Lopuhaä-Zwakenberg

Motivated by mass-spectrometry protein sequencing, we consider a simply-stated problem of reconstructing a string from the multiset of its substring compositions. We show that all strings of length 7, one less than a prime, or one less than…

Discrete Mathematics · Computer Science 2014-03-12 Jayadev Acharya , Hirakendu Das , Olgica Milenkovic , Alon Orlitsky , Shengjun Pan

Is it possible to find a shortest description for a binary string? The well-known answer is "no, Kolmogorov complexity is not computable." Faced with this barrier, one might instead seek a short list of candidates which includes a laconic…

Computational Complexity · Computer Science 2014-02-14 Jason Teutsch

We examine a parameterized complexity class for randomized computation where only the error bound and not the full runtime is allowed to depend more than polynomially on the parameter, based on a proposal by Kwisthout in [15,16]. We prove…

Computational Complexity · Computer Science 2018-11-06 Nils Donselaar

If no optimal propositional proof system exists, we (and independently Pudl\'ak) prove that ruling out length $t$ proofs of any unprovable sentence is hard. This mapping from unprovable to hard-to-prove sentences powerfully translates facts…

Computational Complexity · Computer Science 2023-04-04 Hunter Monroe

We investigate the truth-table degrees of (co-)c.e.\ sets, in particular, sets of random strings. It is known that the set of random strings with respect to any universal prefix-free machine is Turing complete, but that truth-table…

Logic in Computer Science · Computer Science 2015-07-01 Mingzhong Cai , Rodney G Downey , Rachel Epstein , Steffen Lempp , Joseph Miller

A bounded Kolmogorov-Loveland selection rule is an adaptive strategy for recursively selecting a subsequence of an infinite binary sequence; such a subsequence may be interpreted as the query sequence of a time-bounded Turing machine. In…

Computational Complexity · Computer Science 2007-05-23 S. M. Kautz

In this paper, we extend the techniques used in our previous work to show that there exists a probabilistic Turing machine running within time $O(n^k)$ for all $k\in\mathbb{N}_1$ accepting a language $L_d$ that is different from any…

Computational Complexity · Computer Science 2026-05-26 Tianrong Lin

We study probabilistic complexity classes and questions of derandomisation from a logical point of view. For each logic L we introduce a new logic BPL, bounded error probabilistic L, which is defined from L in a similar way as the…

Logic in Computer Science · Computer Science 2015-07-01 Kord Eickmeyer , Martin Grohe

This paper proposes an alternative language for expressing results of the algorithmic theory of randomness. The language is more precise in that it does not involve unspecified additive or multiplicative constants, making mathematical…

Statistics Theory · Mathematics 2020-06-09 Vladimir Vovk

Efficient and accurate low-rank approximation (LRA) methods are of great significance for large-scale data analysis. Randomized tensor decompositions have emerged as powerful tools to meet this need, but most existing methods perform poorly…

Machine Learning · Computer Science 2022-11-29 Yichun Qiu , Weijun Sun , Guoxu Zhou , Qibin Zhao

We develop conjectures and theorems expressing the idea that the prime sequence exhibits computational irreducibility in the transition from one prime to its successor. Informally, given a prime pp p, no general algorithm can compute the…

Computational Complexity · Computer Science 2026-05-14 Ben Goertzel , Bill Lauritzen

We consolidate two widely believed conjectures about tautologies -- no optimal proof system exists, and most require superpolynomial size proofs in any system -- into a $p$-isomorphism-invariant condition satisfied by all paddable…

Computational Complexity · Computer Science 2022-07-21 Hunter Monroe

We show the first unconditional pseudo-determinism result for all of search-BPP. Specifically, we show that every BPP search problem can be computed pseudo-deterministically on average for infinitely many input lengths. In other words, for…

Computational Complexity · Computer Science 2017-07-20 Dhiraj Holden

We correct Miyabe's proof of van Lambalgen's Theorem for truth-table Schnorr randomness (which we will call uniformly relative Schnorr randomness). An immediate corollary is one direction of van Lambalgen's theorem for Schnorr randomness.…

Logic · Mathematics 2013-05-02 Kenshi Miyabe , Jason Rute

We consider a minimal extension of the language of arithmetic, such that the bounded formulas provably total in a suitably-defined theory \`a la Buss (expressed in this new language) precisely capture polytime random functions. Then, we…

Logic in Computer Science · Computer Science 2023-11-28 Melissa Antonelli , Ugo Dal Lago , Davide Davoli , Isabel Oitavem , Paolo Pistone

Drawing on various notions from theoretical computer science, we present a novel numerical approach, motivated by the notion of algorithmic probability, to the problem of approximating the Kolmogorov-Chaitin complexity of short strings. The…

Information Theory · Computer Science 2015-03-13 Fernando Soler-Toscano , Hector Zenil , Jean-Paul Delahaye , Nicolas Gauvrit

We study reductions that limit the extreme adaptivity of Turing reductions. In particular, we study reductions that make a rapid, structured progression through the set to which they are reducing: Each query is strictly longer (shorter)…

Computational Complexity · Computer Science 2007-05-23 Lane A. Hemaspaandra , Mayur Thakur
‹ Prev 1 2 3 10 Next ›