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Within the program of finding axiomatizations for various parts of computability logic, it was proved earlier that the logic of interactive Turing reduction is exactly the implicative fragment of Heyting's intuitionistic calculus. That sort…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

A caveat to many applications of the current Deep Learning approach is the need for large-scale data. One improvement suggested by Kolmogorov Complexity results is to apply the minimum description length principle with computationally…

Machine Learning · Computer Science 2022-08-25 Brieuc Pinon , Raphaël Jungers , Jean-Charles Delvenne

The Turing machine (TM) and the Church thesis have formalized the concept of computable number, this allowed to display non-computable numbers. This paper defines the concept of number "approachable" by a TM and shows that some (if not all)…

Computational Complexity · Computer Science 2010-03-03 Nicolas Brener

We describe the operation of a neuronal device which embodies the computational principles of the `paper-and-pencil' machine envisioned by Alan Turing. The network is based on principles of cortical organization. We develop a plausible…

Neurons and Cognition · Quantitative Biology 2013-12-24 Ariel D Zylberberg , Luciano Paz , Pieter R Roelfsema , Stanislas Dehaene , Mariano Sigman

We investigate Turing's notion of an A-type artificial neural network. We study a refinement of Turing's original idea, motivated by work of Teuscher, Bull, Preen and Copeland. Our A-types can process binary data by accepting and outputting…

Neural and Evolutionary Computing · Computer Science 2011-08-09 Ewan Orr , Ben Martin

Demonstrating quantum advantage in machine learning tasks requires navigating a complex landscape of proposed models and algorithms. To bring clarity to this search, we introduce a framework that connects the structure of parametrized…

Quantum Physics · Physics 2025-12-23 Sergi Masot-Llima , Elies Gil-Fuster , Carlos Bravo-Prieto , Jens Eisert , Tommaso Guaita

Functioning and interaction of distributed devices and concurrent algorithms are analyzed in the context of the theory of algorithms. Our main concern here is how and under what conditions algorithmic interactive devices can be more…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-10-09 Mark Burgin

The purpose of this thesis is to make an analysis of the concept of Hypercomputation and of some hypermachines. This thesis is separated in three main parts. We start in the first chapter with an analysis of the concept of Classical…

Computational Complexity · Computer Science 2012-10-29 Gentian Kasa

It is first pointed out that there is a common mathematical model for the universe and the quantum computer. The former is called the histories approach to quantum mechanics and the latter is called measurement based quantum computation.…

Quantum Physics · Physics 2022-09-01 Stan Gudder

The neural tangent kernel (NTK) has garnered significant attention as a theoretical framework for describing the behavior of large-scale neural networks. Kernel methods are theoretically well-understood and as a result enjoy algorithmic…

Machine Learning · Computer Science 2024-05-30 Jonathan Wenger , Felix Dangel , Agustinus Kristiadi

There has been significant research over the past two decades in developing new platforms for spiking neural computation. Current neural computers are primarily developed to mimick biology. They use neural networks which can be trained to…

Neural and Evolutionary Computing · Computer Science 2015-07-23 Xavier Lagorce , Ryad Benosman

Building on a specific formalization of analogical relationships of the form "A relates to B as C relates to D", we establish a connection between two important subfields of artificial intelligence, namely analogical reasoning and…

Machine Learning · Computer Science 2019-01-09 Mohsen Ahmadi Fahandar , Eyke Hüllermeier

The power of quantum computers is still somewhat speculative. While they are certainly faster than classical ones at some tasks, the class of problems they can efficiently solve has not been mapped definitively onto known classical…

Quantum Physics · Physics 2020-07-09 N. H. Nguyen , E. C. Behrman , M. A. Moustafa , J. E. Steck

We consider the computational model of the Queue Automaton. An old result is that the deterministic queue automaton is equally expressive as the Turing machine. We introduced the Reactive Turing Machine, enhancing the Turing machine with a…

Formal Languages and Automata Theory · Computer Science 2025-02-13 Jos C. M. Baeten , Bas Luttik

A major part of computability theory focuses on the analysis of a few structures of central importance. As a tool, the method of coding with first-order formulas has been applied with great success. For instance, in the c.e. Turing degrees,…

Logic · Mathematics 2013-08-30 Andre Nies

According to some algorithmicists, algorithmics traditionally uses algorithm theory, which stems from mathematics. The growing need for innovative algorithms has caused increasing gaps between theory and practice. Originally, this motivated…

Software Engineering · Computer Science 2020-12-04 Sabah Al-Fedaghi

Quantum computers take advantage of interfering quantum alternatives in order to handle problems that might be too time consuming with algorithms based on classical logic. Developing quantum computers requires new ways of thinking beyond…

Quantum Physics · Physics 2014-09-10 W. C. Parke

Recently, among experiments for realization of quantum computers, NMR quantum computers have achieved the most impressive succession. There is a model of the NMR quantum computation,namely Atsumi and Nishino's bulk quantum Turing Machine.…

Computational Complexity · Computer Science 2007-05-23 Tetsushi Matsui

The uncountability of the real numbers is one of their most basic properties, known (far) outside of mathematics. Cantor's 1874 proof of the uncountability of the real numbers even appears in the very first paper on set theory, i.e. a…

Logic · Mathematics 2022-06-28 Sam Sanders

Computing a consensus object from a set of given objects is a core problem in machine learning and pattern recognition. One popular approach is to formulate it as an optimization problem using the generalized median. Previous methods like…

Computer Vision and Pattern Recognition · Computer Science 2022-09-22 Andreas Nienkötter , Xiaoyi Jiang
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