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In emerging Internet-of-Nano-Thing (IoNT), information will be embedded and conveyed in the form of molecules through complex and diffusive medias. One main challenge lies in the long-tail nature of the channel response causing…

Machine Learning · Computer Science 2019-02-01 Zhuangkun Wei , Weisi Guo , Bin Li , Jerome Charmet , Chenglin Zhao

A non-binary Constraint Satisfaction Problem (CSP) can be solved directly using extended versions of binary techniques. Alternatively, the non-binary problem can be translated into an equivalent binary one. In this case, it is generally…

Artificial Intelligence · Computer Science 2011-09-28 N. Samaras , K. Stergiou

Symmetry is a common feature of many combinatorial problems. Unfortunately eliminating all symmetry from a problem is often computationally intractable. This paper argues that recent parameterized complexity results provide insight into…

Artificial Intelligence · Computer Science 2015-05-19 Toby Walsh

The prime numbers look like a randomly chosen sequence of natural numbers, but there is still no strict theory to determine 'Randomness'. In these years, cryptography has developed a battery of statistical tests for randomness. In this…

Number Theory · Mathematics 2011-02-19 Wang Liang , Huang Yan

Inversion sequences are integer sequences $(\sigma_1, \dots, \sigma_n)$ such that $0 \leqslant \sigma_i < i$ for all $1 \leqslant i \leqslant n$. The study of pattern-avoiding inversion sequences began in two independent articles by…

Combinatorics · Mathematics 2024-07-12 Benjamin Testart

In recent years, the interest in interpretable classification models has grown. One of the proposed ways to improve the interpretability of a rule-based classification model is to use sets (unordered collections) of rules, instead of lists…

Machine Learning · Computer Science 2020-03-31 Thiago Zafalon Miranda , Diorge Brognara Sardinha , Ricardo Cerri

Current methods which compress multisets at an optimal rate have computational complexity that scales linearly with alphabet size, making them too slow to be practical in many real-world settings. We show how to convert a compression…

Information Theory · Computer Science 2023-02-28 Daniel Severo , James Townsend , Ashish Khisti , Alireza Makhzani , Karen Ullrich

Persistence diagrams have been widely used to quantify the underlying features of filtered topological spaces in data visualization. In many applications, computing distances between diagrams is essential; however, computing these distances…

Computational Geometry · Computer Science 2021-08-12 Yu Qin , Brittany Terese Fasy , Carola Wenk , Brian Summa

Biclustering is a class of techniques that simultaneously clusters the rows and columns of a matrix to sort heterogeneous data into homogeneous blocks. Although many algorithms have been proposed to find biclusters, existing methods suffer…

Machine Learning · Statistics 2020-02-11 Michelle N. Ngo , Dustin S. Pluta , Alexander N. Ngo , Babak Shahbaba

We introduce the Insertion Chain Complex, a higher-dimensional extension of insertion graphs, as a new framework for analyzing finite sets of words. We study its topological and combinatorial properties, in particular its homology groups,…

Combinatorics · Mathematics 2025-09-17 Nataša Jonoska , Francisco Martinez-Figueroa , Masahico Saito

Graph clustering under the framework of differential privacy, which aims to process graph-structured data while protecting individual privacy, has been receiving increasing attention. Despite significant achievements in current research,…

Machine Learning · Computer Science 2025-09-09 Haochen You , Baojing Liu

We discuss the use of symmetries for analysing the structural identifiability and observability of control systems. Special emphasis is put on the role of discrete symmetries, in contrast to the more commonly studied continuous or Lie…

We work towards the classification of all one-dimensional exclusion processes with two species of particles that can be solved by a nested coordinate Bethe Ansatz. Using the Yang-Baxter equations, we obtain conditions on the model…

Statistical Mechanics · Physics 2023-07-12 Ivan Lobaskin , Martin R Evans , Kirone Mallick

The notion of symmetry is defined in the context of Linear and Integer Programming. Symmetric integer programs are studied from a group theoretical viewpoint. We investigate the structure of integer solutions of integer programs and show…

Combinatorics · Mathematics 2009-08-25 R. Bödi , K. Herr

Fault-tolerant complexes describe surface-code fault-tolerant protocols from a single geometric object. We first introduce fusion complexes that define a general family of fusion-based quantum computing (FBQC) fault-tolerant quantum…

Consider a data set collected by (individuals-features) pairs in different times. It can be represented as a tensor of three dimensions (Individuals, features and times). The tensor biclustering problem computes a subset of individuals and…

Machine Learning · Computer Science 2019-03-12 Andriantsiory Dina Faneva , Mustapha Lebbah , Hanane Azzag , Gaël Beck

We consider a new family of codes, termed asymmetric Lee distance codes, that arise in the design and implementation of DNA-based storage systems and systems with parallel string transmission protocols. The codewords are defined over a…

Information Theory · Computer Science 2016-12-16 Ryan Gabrys , Han Mao Kiah , Olgica Milenkovic

Stabilizer codes are a simple and successful class of quantum error-correcting codes. Yet this success comes in spite of some harsh limitations on the ability of these codes to fault-tolerantly compute. Here we introduce a new metric for…

Quantum Physics · Physics 2018-05-30 Tomas Jochym-O'Connor , Aleksander Kubica , Theodore J. Yoder

In group testing, simple binary-output tests are designed to identify a small number $t$ of defective items that are present in a large population of $N$ items. Each test takes as input a group of items and produces a binary output…

Information Theory · Computer Science 2017-04-11 Alexander Barg , Arya Mazumdar

Equivariant neural networks incorporate symmetries into their architecture, achieving higher generalization performance. However, constructing equivariant neural networks typically requires prior knowledge of data types and symmetries,…

Machine Learning · Computer Science 2024-10-15 Lexiang Hu , Yikang Li , Zhouchen Lin
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