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Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a precoding step before the polar transform. In this scheme, the polar transform (as a mapper) and the…

Information Theory · Computer Science 2021-03-24 Mohammad Rowshan , Emanuele Viterbo

We consider the concatenation of a convolutional code (CC) with an optimized cyclic redundancy check (CRC) code as a promising paradigm for good short blocklength codes. The resulting CRC-aided convolutional code naturally permits the use…

Information Theory · Computer Science 2022-02-11 Hengjie Yang , Ethan Liang , Minghao Pan , Richard Wesel

In this paper, fundamental limits in sequencing of a set of closely related DNA molecules are addressed. This problem is called pooled-DNA sequencing which encompasses many interesting problems such as haplotype phasing, metageomics, and…

Information Theory · Computer Science 2016-04-20 Amir Najafi , Damoun Nashta-ali , Seyed Abolfazl Motahari , Mehrdad Khani , Babak H. Khalaj , Hamid R. Rabiee

High-rate concatenated quantum codes offer a promising pathway toward fault-tolerant quantum computation, yet designing efficient decoders that fully exploit their error-correction capability remains a significant challenge. In this work,…

Quantum Physics · Physics 2026-01-15 Chao Zhang , Zipeng Wu , Jiahui Wu , Shilin Huang

Decoding sequences that stem from multiple transmissions of a codeword over an insertion, deletion, and substitution channel is a critical component of efficient deoxyribonucleic acid (DNA) data storage systems. In this paper, we consider a…

Information Theory · Computer Science 2020-10-30 Andreas Lenz , Issam Maarouf , Lorenz Welter , Antonia Wachter-Zeh , Eirik Rosnes , Alexandre Graell i Amat

Polar coding gives rise to the first explicit family of codes that provably achieve capacity with efficient encoding and decoding for a wide range of channels. However, its performance at short block lengths is far from optimal. Arikan has…

Information Theory · Computer Science 2021-07-21 Hanwen Yao , Arman Fazeli , Alexander Vardy

Bayesian conformal optimisation methods often use the same held-out data both to search for efficient prediction sets and to certify coverage or risk. This coupling is natural for high-probability risk-control guarantees, but it is not…

Machine Learning · Computer Science 2026-05-19 Fanyi Wu , Lihua Niu , Samuel Kaski , Michele Caprio

A generative Bayesian model is developed for deep (multi-layer) convolutional dictionary learning. A novel probabilistic pooling operation is integrated into the deep model, yielding efficient bottom-up and top-down probabilistic learning.…

Machine Learning · Statistics 2015-02-24 Yunchen Pu , Xin Yuan , Lawrence Carin

Convolutional Neural Networks (CNNs) are well established models capable of achieving state-of-the-art classification accuracy for various computer vision tasks. However, they are becoming increasingly larger, using millions of parameters,…

Computer Vision and Pattern Recognition · Computer Science 2017-07-27 Nikolaos Passalis , Anastasios Tefas

To increase the information capacity of DNA storage, composite DNA letters were introduced. We propose a novel channel model for composite DNA in which composite sequences are decomposed into ordered standard non-composite sequences. The…

Information Theory · Computer Science 2025-10-31 Besart Dollma , Ohad Elishco , Eitan Yaakobi

Assessing the correctness of genome assemblies is an important step in any genome project. Several methods exist, but most are computationally intensive and, in some cases, inappropriate. Here I present baa.pl, a fast and easy-to-use…

Genomics · Quantitative Biology 2014-02-10 Joseph F. Ryan

For decomposable score-based structure learning of Bayesian networks, existing approaches first compute a collection of candidate parent sets for each variable and then optimize over this collection by choosing one parent set for each…

Artificial Intelligence · Computer Science 2017-07-20 Cassio P. de Campos , Mauro Scanagatta , Giorgio Corani , Marco Zaffalon

High read depth can be used to assemble short sequence repeats. The existing genome assemblers fail in repetitive regions of longer than average read. I propose a new algorithm for a DNA assembly which uses the relative frequency of reads…

Genomics · Quantitative Biology 2015-01-08 Robert M. Nowak

To better retain the deep features of an image and solve the sparsity problem of the end-to-end segmentation model, we propose a new deep convolutional network model for medical image pixel segmentation, called MC-Net. The core of this…

Computer Vision and Pattern Recognition · Computer Science 2020-03-26 Hongfeng You , Shengwei Tian , Long Yu , Xiang Ma , Yan Xing , Ning Xin

Concatenating the state-of-the-art codes at moderate rates with repetition codes has emerged as a practical solution deployed in various standards for ultra-low-power devices such as in Internet-of-Things (IoT) networks. In this paper, we…

Information Theory · Computer Science 2022-03-24 Fariba Abbasi , Hessam Mahdavifar , Emanuele Viterbo

Pooled testing is widely used for screening for viral or bacterial infections with low prevalence when individual testing is not cost-efficient. Pooled testing with qualitative assays that give binary results has been well-studied. However,…

Methodology · Statistics 2020-11-03 Tao Liu , Joseph W Hogan , Wanning Su , Yizhen Xu , Michael J Daniels , Kantor Rami

Polar codes were introduced in 2009 by Arikan as the first efficient encoding and decoding scheme that is capacity achieving for symmetric binary-input memoryless channels. Recently, this code family was extended by replacing the…

Information Theory · Computer Science 2018-05-24 Maxime Tremblay , Benjamin Bourassa , David Poulin

A scheme for concatenating the recently invented polar codes with non-binary MDS codes, as Reed-Solomon codes, is considered. By concatenating binary polar codes with interleaved Reed-Solomon codes, we prove that the proposed concatenation…

Information Theory · Computer Science 2016-11-17 Hessam Mahdavifar , Mostafa El-Khamy , Jungwon Lee , Inyup Kang

Despite its reduced complexity, lattice reduction-aided decoding exhibits a widening gap to maximum-likelihood (ML) performance as the dimension increases. To improve its performance, this paper presents randomized lattice decoding based on…

Information Theory · Computer Science 2016-11-17 Shuiyin Liu , Cong Ling , Damien Stehlé

This work identifies information-theoretic quantities that are closely related to the required list size on average for successive cancellation list (SCL) decoding to implement maximum-likelihood decoding over general binary memoryless…

Information Theory · Computer Science 2022-04-04 Mustafa Cemil Coşkun , Henry D. Pfister