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We discuss a class of binary cyclic codes and their dual codes. The minimum distance is determined using algebraic geometry, and an application of Weil's theorem. We relate the weights appearing in the dual codes to the number of rational…

Number Theory · Mathematics 2007-05-23 Gary McGuire , Jose Felipe Voloch

A novel approach to obtain weighted likelihood estimates of multivariate location and scatter is discussed. A weighting scheme is proposed that is based on the distribution of the Mahalanobis distances rather than the distribution of the…

Methodology · Statistics 2017-06-20 Claudio Agostinelli , Luca Greco

We present a new deterministic algorithm for distributed weighted all pairs shortest paths (APSP) in both undirected and directed graphs. Our algorithm runs in $\tilde{O}(n^{4/3})$ rounds in the Congest models on graphs with arbitrary edge…

Data Structures and Algorithms · Computer Science 2020-05-20 Udit Agarwal , Vijaya Ramachandran

In this expository paper we show how one can, in a uniform way, calculate the weight distributions of some well-known binary cyclic codes. The codes are related to certain families of curves, and the weight distributions are related to the…

Number Theory · Mathematics 2016-09-06 René Schoof

The generalized Hamming weight of linear codes is a natural generalization of the minimum Hamming distance. They convey the structural information of a linear code and determine its performance in various applications, and have become one…

Information Theory · Computer Science 2022-12-08 Chao Liu , Dabin Zheng , Xiaoqiang Wang

Estimating the ratio of two probability densities from a finite number of observations is a central machine learning problem. A common approach is to construct estimators using binary classifiers that distinguish observations from the two…

Machine Learning · Computer Science 2025-01-28 Werner Zellinger

In this work, we derive two-sided a posteriori error estimates for the dual-weighted residual (DWR) method. We consider both single and multiple goal functionals. Using a saturation assumption, we derive lower bounds yielding the efficiency…

Numerical Analysis · Mathematics 2018-11-20 Bernhard Endtmayer , Ulrich Langer , Thomas Wick

Some mutually quasi-unbiased weighing matrices are constructed from binary codes satisfying certain conditions. Motivated by this, in this note, we study binary codes satisfying the conditions. The weight distributions of binary codes…

Combinatorics · Mathematics 2016-08-19 Masaaki Harada , Sho Suda

Polarization-adjusted convolutional (PAC) codes combine the polar and convolutional transformations to enhance the distance properties of polar codes. They offer a performance very close to the finite length information-theoretic bounds for…

Information Theory · Computer Science 2022-11-17 Sadra Seyedmasoumian , Tolga M. Duman

Linear codes are widely studied due to their applications in communication, cryptography, quantum codes, distributed storage and many other fields. In this paper, we use the trace and norm functions over finite fields to construct a family…

Information Theory · Computer Science 2024-04-30 Ziling Heng , Mengjie Yang , Yang Ming

We investigate the weight distribution of random binary linear codes. For $0<\lambda<1$ and $n\to\infty$ pick uniformly at random $\lambda n$ vectors in $\mathbb{F}_2^n$ and let $C \le \mathbb{F}_2^n$ be the orthogonal complement of their…

Information Theory · Computer Science 2024-07-11 Nati Linial , Jonathan Mosheiff

Determining the largest size, or equivalently finding the lowest redundancy, of q-ary codes for given length and minimum distance is one of the central and fundamental problems in coding theory. Inspired by the construction of…

Information Theory · Computer Science 2023-10-24 Shu Liu , Chaoping Xing

Many problems of interest for cyber-physical network systems can be formulated as Mixed Integer Linear Programs in which the constraints are distributed among the agents. In this paper we propose a distributed algorithm to solve this class…

Optimization and Control · Mathematics 2017-12-06 Andrea Testa , Alessandro Rucco , Giuseppe Notarstefano

While deep neural networks are a highly successful model class, their large memory footprint puts considerable strain on energy consumption, communication bandwidth, and storage requirements. Consequently, model size reduction has become an…

Machine Learning · Statistics 2018-10-02 Marton Havasi , Robert Peharz , José Miguel Hernández-Lobato

When model predictions inform downstream decision making, a natural question is under what conditions can the decision-makers simply respond to the predictions as if they were the true outcomes. Calibration suffices to guarantee that simple…

Machine Learning · Computer Science 2025-04-23 Jingwu Tang , Jiayun Wu , Zhiwei Steven Wu , Jiahao Zhang

Following a line of work that takes advantage of vast machine-learned data to enhance online algorithms with (possibly erroneous) information about future inputs, we consider predictions in the context of deterministic algorithms for the…

Data Structures and Algorithms · Computer Science 2025-02-17 Christodoulos Karavasilis

We investigate algorithms to find short paths in spatial networks with stochastic edge weights. Our formulation of the problem of finding short paths differs from traditional formulations because we specifically do not make two of the usual…

Social and Information Networks · Computer Science 2013-09-06 Till Hoffmann , Renaud Lambiotte , Mason A. Porter

Few-weight codes have been constructed and studied for many years, since their fascinating relations to finite geometries, strongly regular graphs and Boolean functions. Simplex codes are one-weight Griesmer $[\frac{q^k-1}{q-1},k…

Information Theory · Computer Science 2024-08-20 Xu Pan , Hao Chen , Hongwei Liu , Shengwei Liu

Linear codes with few weights have many applications in secret sharing schemes, authentication codes, communication and strongly regular graphs. In this paper, we consider linear codes with three weights in arbitrary characteristic. To do…

Information Theory · Computer Science 2017-03-27 Sihem Mesnager , Ferruh Özbudak , Ahmet Sınak

In this article, we present a method for increasing adaptivity of an existing robust estimation algorithm by learning two parameters to better fit the residual distribution. The analyzed method uses these two parameters to calculate weights…

Robotics · Computer Science 2023-06-27 Shounak Das , Jason Gross
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