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Stochastic iterative methods are useful in a variety of large-scale numerical linear algebraic, machine learning, and statistical problems, in part due to their low-memory footprint. They are frequently used in a variety of applications,…

Numerical Analysis · Mathematics 2025-11-27 Toby Anderson , Max Collins , Jamie Haddock , Jackie Lok , Elizaveta Rebrova

It is shown that dominant trapping sets of regular LDPC codes, so called absorption sets, undergo a two-phased dynamic behavior in the iterative message-passing decoding algorithm. Using a linear dynamic model for the iteration behavior of…

Information Theory · Computer Science 2015-03-13 Christian Schlegel , Shuai Zhang

We analyse and explain the increased generalisation performance of iterate averaging using a Gaussian process perturbation model between the true and batch risk surface on the high dimensional quadratic. We derive three phenomena…

Machine Learning · Statistics 2021-11-02 Diego Granziol , Xingchen Wan , Samuel Albanie , Stephen Roberts

Speculative decoding is an effective method for lossless acceleration of large language models during inference. It uses a fast model to draft a block of tokens which are then verified in parallel by the target model, and provides a…

Machine Learning · Computer Science 2025-04-14 Ziteng Sun , Uri Mendlovic , Yaniv Leviathan , Asaf Aharoni , Jae Hun Ro , Ahmad Beirami , Ananda Theertha Suresh

An algorithm of improving the performance of iterative decoding on perpendicular magnetic recording is presented. This algorithm follows on the authors' previous works on the parallel and serial concatenated turbo codes and low-density…

Information Theory · Computer Science 2007-07-13 E. Papagiannis , C. Tjhai , M. Ahmed , M. Ambroze , M. Tomlinson

This two-part paper discusses robustification methodologies for linear-iterative distributed algorithms for consensus and coordination problems in multicomponent systems, in which unreliable communication links may drop packets. We consider…

Systems and Control · Computer Science 2011-09-30 Alejandro D. Dominguez-Garcia , Christoforos N. Hadjicostis , Nitin H. Vaidya

We propose a new class of information-coupled (IC) Turbo codes to improve the transport block (TB) error rate performance for long-term evolution (LTE) systems, while keeping the hybrid automatic repeat request protocol and the Turbo…

Information Theory · Computer Science 2017-09-21 Lei Yang , Yixuan Xie , Xiaowei Wu , Jinhong Yuan , Xingqing Cheng , Lei Wan

Binary turbo product codes (TPCs) are powerful error-correcting codes constructed from short component codes. Traditionally, turbo product decoding passes log likelihood ratios (LLRs) between the component decoders, inherently losing…

Information Theory · Computer Science 2025-11-12 Lukas Rapp , Muriel Médard , Ken R. Duffy

Iterative algorithms are widely used in digital signal processing applications. With the case study of radio astronomy calibration processing, this work contributes towards revealing and exploiting the intrinsic error resilience of…

Signal Processing · Electrical Eng. & Systems 2025-02-21 G. A. Gillani , A. Krapukhin , A. B. J. Kokkeler

We propose a novel soft-aided iterative decoding algorithm for product codes (PCs). The proposed algorithm, named iterative bounded distance decoding with combined reliability (iBDD-CR), enhances the conventional iterative bounded distance…

Information Theory · Computer Science 2021-09-08 Alireza Sheikh , Alexandre Graell i Amat , Gianluigi Liva , Alex Alvarado

A frequently faced task in experimental physics is to measure the probability distribution of some quantity. Often this quantity to be measured is smeared by a non-ideal detector response or by some physical process. The procedure of…

Statistics Theory · Mathematics 2014-04-11 Andras Laszlo

Efficient and realistic error decoding is crucial for fault-tolerant quantum computation (FTQC) on near-term devices. While decoding is a classical post-processing task, its effectiveness depends on accurately modeling quantum noise, which…

Quantum Physics · Physics 2025-09-10 Yi Tian , Y. Zheng , Xiaoting Wang , Ching-Yi Lai

The z-transform of a sequence is a classical tool used within signal processing, control theory, computer science, and electrical engineering. It allows for studying sequences from their generating functions, with many operations that can…

Machine Learning · Computer Science 2025-07-18 Francis Bach

We study iterative blind symbol detection for block-fading linear inter-symbol interference channels. Based on the factor graph framework, we design a joint channel estimation and detection scheme that combines the expectation maximization…

Information Theory · Computer Science 2024-08-06 Luca Schmid , Tomer Raviv , Nir Shlezinger , Laurent Schmalen

Iterative decoding is essential in modern communication systems, especially optical communications, where error-correcting codes such as turbo product codes (TPC) and staircase codes are widely employed. A key factor in achieving high error…

Information Theory · Computer Science 2025-06-06 Dmitry Artemasov , Oleg Nesterenkov , Kirill Andreev , Pavel Rybin , Alexey Frolov

The error floor phenomenon observed with LDPC codes and their graph-based, iterative, message-passing (MP) decoders is commonly attributed to the existence of error-prone substructures -- variously referred to as near codewords, trapping…

Information Theory · Computer Science 2013-09-11 Xiaojie Zhang , Paul H. Siegel

For material identification, characterization, and quantification, it is useful to estimate system-independent material properties that do not depend on the detailed specifications of the X-ray computed tomography (CT) system such as…

Materials Science · Physics 2022-04-04 K. Aditya Mohan , Kyle M. Champley , Albert W. Reed , Steven M. Glenn , Harry E. Martz

In all applications in digital communications, it is crucial for an estimator to be unbiased. Although so-called soft feedback is widely employed in many different fields of engineering, typically the biased estimate is used. In this paper,…

Information Theory · Computer Science 2018-02-21 Susanne Sparrer , Robert F. H. Fischer

Diffusion Transformers (DiTs) have demonstrated remarkable generative capabilities, particularly benefiting from Transformer architectures that enhance visual and artistic fidelity. However, their inherently sequential denoising process…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Hanqi Chen , Xu Zhang , Xiaoliu Guan , Lielin Jiang , Guanzhong Wang , Zeyu Chen , Yi Liu

The click-through rate (CTR) reflects the ratio of clicks on a specific item to its total number of views. It has significant impact on websites' advertising revenue. Learning sophisticated models to understand and predict user behavior is…

Machine Learning · Computer Science 2020-07-29 Amit Livne , Roy Dor , Eyal Mazuz , Tamar Didi , Bracha Shapira , Lior Rokach