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In many situations, sample data is obtained from a noisy or imperfect source. In order to address such corruptions, this paper introduces the concept of a sampling corrector. Such algorithms use structure that the distribution is purported…

Data Structures and Algorithms · Computer Science 2018-04-03 Clément Canonne , Themis Gouleakis , Ronitt Rubinfeld

Multi-modal hashing methods have gained popularity due to their fast speed and low storage requirements. Among them, the supervised methods demonstrate better performance by utilizing labels as supervisory signals compared with unsupervised…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Jin-Yu Liu , Xian-Ling Mao , Tian-Yi Che , Rong-Cheng Tu

Bosonic cat qubits stabilized by two-photon driven dissipation benefit from exponential suppression of bit-flip errors and an extensive set of gates preserving this protection. These properties make them promising building blocks of a…

Deep Neural Networks (DNNs) have been shown to be susceptible to memorization or overfitting in the presence of noisily-labelled data. For the problem of robust learning under such noisy data, several algorithms have been proposed. A…

Machine Learning · Computer Science 2022-12-06 Deep Patel , P. S. Sastry

Guessing random additive noise decoding (GRAND) algorithm has emerged as an excellent decoding strategy that can meet both the high reliability and low latency constraints. This paper proposes a successive addition-subtraction algorithm to…

Information Theory · Computer Science 2021-11-02 Ming Zhan , Zhibo Pang , Kan Yu , Jing Xu , Fang Wu

The trend of increasing cluster sizes of supercomputers leads to a growing susceptibility to Silent Data Corruption (SDC) that can invalidate program results. A common strategy for SDC protection is replication, where the computation is…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-29 Mia Reitz , Claudia Fohry

Secure storage of noisy data for authentication purposes usually involves the use of error correcting codes. We propose a new model scenario involving burst errors and present for that several constructions.

Information Theory · Computer Science 2012-05-24 Felix Fontein , Kyle Marshall , Joachim Rosenthal , Davide Schipani , Anna-Lena Trautmann

We construct two simple error correction schemes adapted to amplitude damping noise for Bacon-Shor codes and investigate their prospects for fault-tolerant implementation. Both consist solely of Clifford gates and require far fewer qubits,…

Quantum Physics · Physics 2017-12-27 Álvaro Piedrafita , Joseph M. Renes

Customer data is often stored as records in Customer Relations Management systems (CRMs). Data which is manually entered into such systems by one of more users over time leads to data replication, partial duplication or fuzzy duplication.…

Computation and Language · Computer Science 2024-06-25 Ian Ormesher

The short lifespan of traditional data storage media, coupled with an exponential increase in storage demand, has made long-term archival a fundamental problem in the data storage industry and beyond. Consequently, researchers are looking…

Image and Video Processing · Electrical Eng. & Systems 2026-03-06 Xavier Pic , Nimesh Pinnamaneni , Raja Appuswamy

We study the performance of simple quantum error correcting codes with respect to correlated noise errors characterized by a finite correlation strength. Specifically, we consider bit flip (phase flip) noisy quantum memory channels and use…

Quantum Physics · Physics 2015-05-13 Carlo Cafaro , Stefano Mancini

The problem of correcting deletions and insertions has recently received significantly increased attention due to the DNA-based data storage technology, which suffers from deletions and insertions with extremely high probability. In this…

Information Theory · Computer Science 2023-11-09 Tuan Thanh Nguyen , Kui Cai , Paul H. Siegel

High quality labeled datasets have allowed deep learning to achieve impressive results on many sound analysis tasks. Yet, it is labor-intensive to accurately annotate large amount of audio data, and the dataset may contain noisy labels in…

Audio and Speech Processing · Electrical Eng. & Systems 2020-07-17 Boqing Zhu , Kele Xu , Qiuqiang Kong , Huaimin Wang , Yuxing Peng

Motivated by DNA storage systems and 3D fingerprinting, this work studies the adversarial torn paper channel with edit errors. This channel first applies at most $t_e$ edit errors (i.e., insertions, deletions, and substitutions) to the…

Information Theory · Computer Science 2026-01-21 Maria Abu-Sini , Reinhard Heckel

Deep neural networks rely heavily on normalization methods to improve their performance and learning behavior. Although normalization methods spurred the development of increasingly deep and efficient architectures, they also increase the…

Machine Learning · Computer Science 2021-10-06 Alexander Fuchs , Christian Knoll , Franz Pernkopf

Quantum error correction is widely believed to be essential for large-scale quantum computation, but the required qubit overhead remains a central challenge. Quantum low-density parity-check codes can substantially reduce this overhead…

Quantum Physics · Physics 2026-05-13 Chen Zhao , Casey Duckering , Andi Gu , Nishad Maskara , Hengyun Zhou

We apply a dynamical systems approach to concatenation of quantum error correcting codes, extending and generalizing the results of Rahn et al. [1] to both diagonal and nondiagonal channels. Our point of view is global: instead of focusing…

Quantum Physics · Physics 2007-05-23 Jesse Fern , Julia Kempe , Slobodan Simic , Shankar Sastry

Burst errors involving simultaneous insertions, deletions, and substitutions occur in practical scenarios, including DNA data storage and document synchronization, motivating developments of channel codes that can correct such errors. In…

Information Theory · Computer Science 2026-01-23 Yajuan Liu , Tolga M. Duman

The angular synchronization problem aims to accurately estimate (up to a constant additive phase) a set of unknown angles $\theta_1, \dots, \theta_n\in[0, 2\pi)$ from $m$ noisy measurements of their offsets $\theta_i-\theta_j \;\mbox{mod}…

Machine Learning · Computer Science 2024-02-13 Yixuan He , Gesine Reinert , David Wipf , Mihai Cucuringu

We study data structures in the presence of adversarial noise. We want to encode a given object in a succinct data structure that enables us to efficiently answer specific queries about the object, even if the data structure has been…

Data Structures and Algorithms · Computer Science 2008-12-01 Ronald de Wolf
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