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Related papers: Approximation of the Two-Part MDL Code

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Compression and generalization are fundamentally related through Solomonoff induction and the minimum description length principle (MDL), which predict that simpler models generalize better when data arises from low-complexity…

Machine Learning · Computer Science 2026-05-14 Lukas Silvester Barth , Paulo von Petersenn

The Minimum Description Length (MDL) principle selects the model that has the shortest code for data plus model. We show that for a countable class of models, MDL predictions are close to the true distribution in a strong sense. The result…

Probability · Mathematics 2010-12-30 Marcus Hutter

We consider recursive decoding techniques for RM codes, their subcodes, and newly designed codes. For moderate lengths up to 512, we obtain near-optimum decoding with feasible complexity.

Information Theory · Computer Science 2017-03-17 Ilya Dumer , Kirill Shabunov

Linear computation coding is concerned with the compression of multidimensional linear functions, i.e. with reducing the computational effort of multiplying an arbitrary vector to an arbitrary, but known, constant matrix. This paper…

Information Theory · Computer Science 2025-07-02 Hans Rosenberger , Johanna S. Fröhlich , Ali Bereyhi , Ralf R. Müller

We define the bidirectional distance profile (BDP) of a convolutional code as the minimum of the distance profiles of the code and its corresponding "reverse" code. We present tables of codes with the optimum BDP (OBDP), which minimize the…

Information Theory · Computer Science 2023-11-30 Ivan Stanojević , Vojin Šenk

The minimum distance of a code is an important concept in information theory. Hence, computing the minimum distance of a code with a minimum computational cost is a crucial process to many problems in this area. In this paper, we present…

Information Theory · Computer Science 2024-05-01 Fernando Hernando , Francisco D. Igual , Gregorio Quintana-Ortí

In this paper, we propose a column by column encoding scheme suitable for two-dimensional (2D) constraint codes and derive a lower bound of its maximum achievable rate. It is shown that the maximum achievable rate is equal to the largest…

Information Theory · Computer Science 2018-04-18 Kazuya Hirata , Tadashi Wadayama

We consider locally repairable codes over small fields and propose constructions of optimal cyclic and linear codes in terms of the dimension for a given distance and length. Four new constructions of optimal linear codes over small fields…

Information Theory · Computer Science 2016-11-17 Alexander Zeh , Eitan Yaakobi

Quasi-Monte Carlo algorithms are studied for designing discrete approximations of two-stage linear stochastic programs. Their integrands are piecewise linear, but neither smooth nor lie in the function spaces considered for QMC error…

Optimization and Control · Mathematics 2014-10-31 H. Heitsch , H. Leövey , W. Römisch

The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss terms on the node's activations. The first loss term imposes a…

Information Theory · Computer Science 2022-08-12 Eliya Nachmani , Yair Be'ery

In fully dynamic graphs, we know how to maintain a 2-approximation of maximum matching extremely fast, that is, in polylogarithmic update time or better. In a sharp contrast and despite extensive studies, all known algorithms that maintain…

Data Structures and Algorithms · Computer Science 2019-11-06 Soheil Behnezhad , Jakub Łącki , Vahab Mirrokni

Link prediction in graphs is an important task in the fields of network science and machine learning. We investigate a flexible means of regularization for link prediction based on an approximation of the Kolmogorov complexity of graphs…

Machine Learning · Computer Science 2021-02-24 Paris D. L. Flood , Ramon Viñas , Pietro Liò

We consider the problem of designing optimal linear codes (in terms of having the largest minimum distance) subject to a support constraint on the generator matrix. We show that the largest minimum distance can be achieved by a subcode of a…

Information Theory · Computer Science 2018-03-13 Hikmet Yildiz , Babak Hassibi

Monotonicity is a simple yet significant qualitative characteristic. We consider the problem of segmenting a sequence in up to K segments. We want segments to be as monotonic as possible and to alternate signs. We propose a quality metric…

Databases · Computer Science 2009-09-01 Daniel Lemire , Martin Brooks , Yuhong Yan

Complexity is a fundamental concept underlying statistical learning theory that aims to inform generalization performance. Parameter count, while successful in low-dimensional settings, is not well-justified for overparameterized settings…

Machine Learning · Computer Science 2023-10-16 Raaz Dwivedi , Chandan Singh , Bin Yu , Martin J. Wainwright

Huffman coding finds an optimal prefix code for a given probability mass function. Consider situations in which one wishes to find an optimal code with the restriction that all codewords have lengths that lie in a user-specified set of…

Information Theory · Computer Science 2008-01-03 Michael B. Baer

Field experiments are often difficult and expensive to make. To bypass these issues, industrial companies have developed computational codes. These codes intend to be representative of the physical system, but come with a certain amount of…

Computation · Statistics 2019-03-26 Mathieu Carmassi , Pierre Barbillon , Merlin Keller , Eric Parent , Matthieu Chiodetti

A construction of 2-quasi-perfect Lee codes is given over the space $\mathbb Z_p^n$ for $p$ prime, $p\equiv \pm 5\pmod{12}$ and $n=2[\frac{p}{4}]$. It is known that there are infinitely many such primes. Golomb and Welch conjectured that…

Information Theory · Computer Science 2017-06-26 Cristóbal Camarero , Carmen Martínez

The MDL two-part coding $ \textit{index of resolvability} $ provides a finite-sample upper bound on the statistical risk of penalized likelihood estimators over countable models. However, the bound does not apply to unpenalized maximum…

Statistics Theory · Mathematics 2018-01-01 W. D. Brinda , Jason M. Klusowski

While Kolmogorov complexity is the accepted absolute measure of information content of an individual finite object, a similarly absolute notion is needed for the relation between an individual data sample and an individual model summarizing…

Statistics Theory · Mathematics 2007-07-16 Peter Gacs , John Tromp , Paul Vitanyi