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Many clustering schemes are defined by optimizing an objective function defined on the partitions of the underlying set of a finite metric space. In this paper, we construct a framework for studying what happens when we instead impose…

Machine Learning · Statistics 2010-12-01 Gunnar Carlsson , Facundo Memoli

Probabilistic programming is a growing area that strives to make statistical analysis more accessible, by separating probabilistic modelling from probabilistic inference. In practice this decoupling is difficult. No single inference…

Programming Languages · Computer Science 2022-04-15 Maria I. Gorinova

Computing according to laymens procedures is changed to contain a paradigm of inoptimality in the high level and assembled code. The code is changed to maximize the flow of information contained in the electrons so that they function more…

General Physics · Physics 2007-05-23 Gordon Chalmers

Computational mechanics quantifies structure in a stochastic process via its causal states, leading to the process's minimal, optimal predictor---the $\epsilon$-machine. We extend computational mechanics to communication channels between…

Statistical Mechanics · Physics 2016-01-27 Nix Barnett , James P. Crutchfield

We develop a correspondence between the theory of sequential algorithms and classical reasoning, via Kreisel's no-counterexample interpretation. Our framework views realizers of the no-counterexample interpretation as dynamic processes…

Logic in Computer Science · Computer Science 2018-12-31 Thomas Powell

In the rapidly growing literature on explanation algorithms, it often remains unclear what precisely these algorithms are for and how they should be used. In this position paper, we argue for a novel and pragmatic perspective: Explainable…

Machine Learning · Computer Science 2025-06-17 Sebastian Bordt , Eric Raidl , Ulrike von Luxburg

We propose a notion of state distinguishability that does not refer to probabilities, but rather to the ability of a set of states to serve as programs for a desired set of gates. Using this notion, we reconstruct the structural features of…

Quantum Physics · Physics 2015-05-01 Giulio Chiribella

Programs with control are usually modeled using lambda calculus extended with control operators. Instead of modifying lambda calculus, we consider a different model of computation. We introduce continuation calculus, or CC, a deterministic…

Logic in Computer Science · Computer Science 2013-09-06 Bram Geron , Herman Geuvers

We introduce an object-oriented framework for parallel programming, which is based on the observation that programming objects can be naturally interpreted as processes. A parallel program consists of a collection of persistent processes…

Programming Languages · Computer Science 2014-04-21 Edward Givelberg

Research efforts of the past fifty years have led to a development of linear integer programming as a mature discipline of mathematical optimization. Such a level of maturity has not been reached when one considers nonlinear systems subject…

Optimization and Control · Mathematics 2017-01-03 Raymond Hemmecke , Matthias Köppe , Jon Lee , Robert Weismantel

A logic program is an executable specification. For example, merge sort in pure Prolog is a logical formula, yet shows creditable performance on long linked lists. But such executable specifications are a compromise: the logic is distorted…

Programming Languages · Computer Science 2015-09-29 M. H. van Emden

People solve different problems and know that some of them are simple, some are complex and some insoluble. The main goal of this work is to develop a mathematical theory of algorithmic complexity for problems. This theory is aimed at…

Computational Complexity · Computer Science 2008-07-08 Mark Burgin

Algorithmic statistics considers the following problem: given a binary string $x$ (e.g., some experimental data), find a "good" explanation of this data. It uses algorithmic information theory to define formally what is a good explanation.…

Machine Learning · Computer Science 2015-09-21 Alexey Milovanov

In a previous paper, we provided a formal definition for the concept of computational irreducibility (CIR), i.e. the fact for a function f from N to N that it is impossible to compute f(n) without following approximately the same path than…

Computational Complexity · Computer Science 2013-10-15 Herve Zwirn

A plausible definition of "reasoning" could be "algebraically manipulating previously acquired knowledge in order to answer a new question". This definition covers first-order logical inference or probabilistic inference. It also includes…

Artificial Intelligence · Computer Science 2011-02-14 Leon Bottou

Probably building non procedural languages is the most prospective way for parallel programming just because non procedural means no fixed way for execution. The article consists of 3 parts. In first part we consider formal systems for…

Distributed, Parallel, and Cluster Computing · Computer Science 2008-11-03 Renat Nuriyev

A computer code or simulator is a mathematical representation of a physical system, for example a set of differential equations. Running the code with given values of the vector of inputs, x, leads to an output y(x) or several such outputs.…

Methodology · Statistics 2016-01-25 Derek Bingham , Pritam Ranjan , William Welch

We present a necessary and sufficient condition for a 3 by 3 matrix to be unitarily equivalent to a symmetric matrix with complex entries, and an algorithm whereby an arbitrary 3 by 3 matrix can be tested. This test generalizes to a…

Functional Analysis · Mathematics 2009-08-18 James E. Tener

We discuss a formal system of mathematics. We use it to construct the natural numbers.

Logic · Mathematics 2020-04-10 Christoph Thiele

In the context of Higman embeddings of recursive groups into finitely presented groups we suggest an algorithm which uses Higman operations to explicitly constructs the specific recursively enumerable sets of integer sequences arising…

Group Theory · Mathematics 2023-10-18 V. H. Mikaelian