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A new class of spatially-coupled turbo-like codes (SC-TCs), dubbed generalized spatially coupled parallel concatenated codes (GSC-PCCs), is introduced. These codes are constructed by applying spatial coupling on parallel concatenated codes…

Information Theory · Computer Science 2022-02-25 Min Qiu , Xiaowei Wu , Jinhong Yuan , Alexandre Graell i Amat

We present a novel framework, called balanced overlay networks (BON), that provides scalable, decentralized load balancing for distributed computing using large-scale pools of heterogeneous computers. Fundamentally, BON encodes the…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Jesse S. A. Bridgewater , P. Oscar Boykin , Vwani P. Roychowdhury

This paper presents a novel type-II hybrid automatic repeat request (HARQ) transmission scheme which is based on pruned convolutional codes (CCs) and supports unequal error protection (UEP). The data to be transmitted is assumed to consist…

Information Theory · Computer Science 2015-09-30 Annabel Sharon Shitrit , Yonathan Murin , Ron Dabora , Osnat Keren

We investigate a class of chance-constrained combinatorial optimization problems. Given a pre-specified risk level $\epsilon \in [0,1]$, the chance-constrained program aims to find the minimum cost selection of a vector of binary decisions…

Optimization and Control · Mathematics 2020-06-02 Hao-Hsiang Wu , Simge Kucukyavuz

In this paper, we investigate the impact of spatial coupling on the thresholds of turbo-like codes. Parallel concatenated and serially concatenated convolutional codes as well as braided convolutional codes (BCCs) are compared by means of…

Information Theory · Computer Science 2014-07-03 Michael Lentmaier , Saeedeh Moloudi , Alexandre Graell i Amat

Feature pooling layers (e.g., max pooling) in convolutional neural networks (CNNs) serve the dual purpose of providing increasingly abstract representations as well as yielding computational savings in subsequent convolutional layers. We…

Machine Learning · Computer Science 2016-11-17 Shuangfei Zhai , Hui Wu , Abhishek Kumar , Yu Cheng , Yongxi Lu , Zhongfei Zhang , Rogerio Feris

Identifying concentrations of components from an observed mixture is a fundamental problem in signal processing. It has diverse applications in fields ranging from hyperspectral imaging to denoising biomedical sensors. This paper focuses on…

Computational Engineering, Finance, and Science · Computer Science 2016-11-17 Shahin Mohammadi , Neta Zuckerman , Andrea Goldsmith , Ananth Grama

In this paper, we introduce a novel class of pre-transformed polar codes, termed as deep polar codes. We first present a deep polar encoder that harnesses a series of multi-layered polar transformations with varying sizes. Our approach to…

Information Theory · Computer Science 2023-08-08 Geon Choi , Namyoon Lee

Mathematical methods together with measurements of single-cell dynamics provide unprecedented means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions the…

Quantitative Methods · Quantitative Biology 2014-01-14 Christoph Zechner , Michael Unger , Serge Pelet , Matthias Peter , Heinz Koeppl

Convolutional precoding in polarization-adjusted convolutional (PAC) codes is a recently introduced variant of polar codes. It has demonstrated an effective reduction in the number of minimum weight codewords (a.k.a error coefficient) of…

Information Theory · Computer Science 2024-06-05 Xinyi Gu , Mohammad Rowshan , Jinhong Yuan

We propose a new compression scheme for genomic data given as sequence fragments called reads. The scheme uses a reference genome at the decoder side only, freeing the encoder from the burdens of storing references and performing…

Information Theory · Computer Science 2023-02-10 Yotam Gershon , Yuval Cassuto

Performance and complexity of sequential decoding of polarization-adjusted convolutional (PAC) codes is studied. In particular, a performance and computational complexity comparison of PAC codes with 5G polar codes and convolutional codes…

Information Theory · Computer Science 2020-12-18 Mohsen Moradi , Amir Mozammel , Kangjian Qin , Erdal Arikan

Alignment has greatly improved large language models (LLMs)' output quality at the cost of diversity, yielding highly similar outputs across generations. We propose Base-Aligned Model Collaboration (BACo), an inference-time token-level…

Computation and Language · Computer Science 2025-11-11 Yichen Wang , Chenghao Yang , Tenghao Huang , Muhao Chen , Jonathan May , Mina Lee

Concatenation is a method of building long codes out of shorter ones, it attempts to meet the problem of decoding complexity by breaking the required computation into manageable segments. Concatenated Continuous Phase Frequency Shift Keying…

Information Theory · Computer Science 2011-05-24 Labib Francis Gergis

Haplotype-resolved de novo assembly is the ultimate solution to the study of sequence variations in a genome. However, existing algorithms either collapse heterozygous alleles into one consensus copy or fail to cleanly separate the…

Genomics · Quantitative Biology 2021-02-03 Haoyu Cheng , Gregory T Concepcion , Xiaowen Feng , Haowen Zhang , Heng Li

Low-density parity-check (LDPC) convolutional codes have been shown to exhibit excellent performance under low-complexity belief-propagation decoding [1], [2]. This phenomenon is now termed threshold saturation via spatial coupling. The…

Information Theory · Computer Science 2013-12-30 Santhosh Kumar , Andrew J. Young , Nicolas Macris , Henry D. Pfister

An approximation to the ~4 Mbp basic genome shared by 32 strains of E. coli representing six evolutionary groups has been derived and analyzed computationally. A multiple-alignment of the 32 complete genome sequences was filtered to remove…

Genomics · Quantitative Biology 2016-02-17 Purushottam Dixit , Tin Yau Pang , F. William Studier , Sergei Maslov

An iterative decoding algorithm for convolutional codes is presented. It successively processes $N$ consecutive blocks of the received word in order to decode the first block. A bound is presented showing which error configurations can be…

Information Theory · Computer Science 2009-08-07 H. Gluesing-Luerssen , U. Helmke , J. I. Iglesias Curto

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combination of codes, code-rates and decoding techniques. In the…

Information Theory · Computer Science 2020-10-16 Alejandro Cohen , Amit Solomon , Ken R. Duffy , Muriel Médard

We present an optimal method for encoding cluster assignments of arbitrary data sets. Our method, Random Cycle Coding (RCC), encodes data sequentially and sends assignment information as cycles of the permutation defined by the order of…

Machine Learning · Computer Science 2024-12-03 Daniel Severo , Ashish Khisti , Alireza Makhzani
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