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Related papers: The Combinatorics of Occam's Razor

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This paper's first aim is to prove a modernized Occam's razor beyond a reasonable doubt. To summarize the main argument in one sentence: If we consider all possible, intelligible, scientific models of ever-higher complexity, democratically,…

Information Theory · Computer Science 2025-07-03 Gabriel Leuenberger

A formal theory of simplicity is introduced, in the context of a "combinational" computation model that views computation as comprising the iterated transformational and compositional activity of a population of agents upon each other.…

Artificial Intelligence · Computer Science 2020-09-04 Ben Goertzel

The task of parametric model selection is cast in terms of a statistical mechanics on the space of probability distributions. Using the techniques of low-temperature expansions, we arrive at a systematic series for the Bayesian posterior…

Condensed Matter · Physics 2008-02-03 Vijay Balasubramanian

Statistical learning theory is often associated with the principle of Occam's razor, which recommends a simplicity preference in inductive inference. This paper distills the core argument for simplicity obtainable from statistical learning…

Machine Learning · Computer Science 2024-12-02 Tom F. Sterkenburg

Ensemble theories have received a lot of interest recently as a means of explaining a lot of the detailed complexity observed in reality by a vastly simpler description ``every possibility exists'' and a selection principle ({\em Anthropic…

General Physics · Physics 2015-06-26 Russell K. Standish

The problem of ranking can be described as follows. We have a set of combinatorial objects $S$, such as, say, the k-subsets of n things, and we can imagine that they have been arranged in some list, say lexicographically, and we want to…

Computational Complexity · Computer Science 2007-05-23 Boris Ryabko

One way of studying a relational structure is to investigate functions which are related to that structure and which leave certain aspects of the structure invariant. Examples are the automorphism group, the self-embedding monoid, the…

Logic · Mathematics 2011-05-31 Manuel Bodirsky , Michael Pinsker

We introduce the principle of Occam's Razor in a form which can be used as a basis for economical formulations of physics. This allows us to explain the general structure of the Lagrangian for a composite physical system, as well as some…

Mathematical Physics · Physics 2016-09-07 Andrei N. Soklakov

Prompted by misconceptions in the recent literature, we review the justifications for naturalness arguments and Occam's razor found in Bayesian statistics. We discuss the automatic Occam's razor that emerges in Bayesian formalism, bringing…

History and Philosophy of Physics · Physics 2026-04-22 Andrew Fowlie

In this note we introduce linear regression with basis functions in order to apply Bayesian model selection. The goal is to incorporate Occam's razor as provided by Bayes analysis in order to automatically pick the model optimally able to…

Statistics Theory · Mathematics 2015-12-16 Miguel de Benito Delgado , Philipp Wacker

Given an undirected graph representing similarities between a set of items and an additive measure evaluating the items, we treat the position of a special subset of items in an ordinal ranking through a collection of combinatorial…

Data Structures and Algorithms · Computer Science 2026-05-05 Samuel Boardman

The Bayes factor is the gold-standard figure of merit for comparing fits of models to data, for hypothesis selection and parameter estimation. However it is little used because it is computationally very intensive. Here it is shown how…

Data Analysis, Statistics and Probability · Physics 2020-07-21 David J. Dunstan , Joel Crowne , Alan J. Drew

Bayesian inference provides a uniquely rigorous approach to obtain principled justification for uncertainty in predictions, yet it is difficult to articulate suitably general prior belief in the machine learning context, where computational…

Machine Learning · Statistics 2021-03-04 Jed A. Duersch , Thomas A. Catanach

We consider colored compositions where only some parts are allowed different colors, depending on their locations in the composition. The counting sequences are obtained through generating functions. Connections to many other combinatorial…

Combinatorics · Mathematics 2025-11-12 Andrew Li , Hua Wang

This paper is dedicated to a robust ordinal method for learning the preferences of a decision maker between subsets. The decision model, derived from Fishburn and LaValle (1996) and whose parameters we learn, is general enough to be…

Artificial Intelligence · Computer Science 2023-08-08 Hugo Gilbert , Mohamed Ouaguenouni , Meltem Ozturk , Olivier Spanjaard

Combinatorics, like computer science, often has to deal with large objects of unspecified (or unusable) structure. One powerful way to deal with such an arbitrary object is to decompose it into more usable components. In particular, it has…

Combinatorics · Mathematics 2011-11-10 Terence Tao

This document presents a combinatorial framework for analyzing assembly systems using generating functions. We explore the theory through concrete examples, such as linear polymers, and develop recursive equations to characterize valid…

Combinatorics · Mathematics 2025-01-22 Andrés Ortiz-Muñoz

For any given Cuntz semigroup, we introduce a function associated to it, called the ``Rank Ratio Function". This function ensures global control over the oscillation of the rank of any pair of elements in the Cuntz semigroup and, also,…

Operator Algebras · Mathematics 2025-06-13 M. Ali Asadi-Vasfi

In this paper we initiate the study of racks from the combined perspective of combinatorics and finite group theory. A rack R is a set with a self-distributive binary operation. We study the combinatorics of the partially ordered set {\cal…

Combinatorics · Mathematics 2015-12-07 Istvan Heckenberger , John Shareshian , Volkmar Welker

We are often interested in decomposing complex, structured data into simple components that explain the data. The linear version of this problem is well-studied as dictionary learning and factor analysis. In this work, we propose a…

Machine Learning · Computer Science 2024-07-29 Avrim Blum , Kavya Ravichandran
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