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Packing and covering semidefinite programs (SDPs) appear in natural relaxations of many combinatorial optimization problems as well as a number of other applications. Recently, several techniques were proposed, that utilize the particular…

Data Structures and Algorithms · Computer Science 2019-02-19 Khaled Elbassioni , Kazuhisa Makino

In his thesis, Wiberg showed the existence of thresholds for families of regular low-density parity-check codes under min-sum algorithm decoding. He also derived analytic bounds on these thresholds. In this paper, we formulate similar…

Information Theory · Computer Science 2007-07-16 Ralf Koetter , Pascal O. Vontobel

Quantum algorithms offer significant speed-ups over their classical counterparts in various applications. In this paper, we develop quantum algorithms for the Kalman filter widely used in classical control engineering using the block…

Quantum Algebra · Mathematics 2024-04-09 Hao Shi , Guofeng Zhang , Ming Zhang

In this work, we present hardware and software implementations of flexible polar systematic encoders and decoders. The proposed implementations operate on polar codes of any length less than a maximum and of any rate. We describe the…

Information Theory · Computer Science 2016-08-29 Gabi Sarkis , Ido Tal , Pascal Giard , Alexander Vardy , Claude Thibeault , Warren J. Gross

This paper investigates linear-time decoding algorithms for two classes of error-correcting codes. One of the classes is monotone codes which are known as single deletion codes. The other is azinv codes which are known as single balanced…

Information Theory · Computer Science 2020-04-16 Hokuto Takahashi , Manabu Hagiwara

Inference latency stands as a critical bottleneck in the large-scale deployment of Large Language Models (LLMs). Speculative decoding methods have recently shown promise in accelerating inference without compromising the output…

Machine Learning · Computer Science 2025-10-31 Ruilin Wang , Huixia Li , Yuexiao Ma , Xiawu Zheng , Fei Chao , Xuefeng Xiao , Rongrong Ji

Qualitative data analysis provides insight into the underlying perceptions and experiences within unstructured data. However, the time-consuming nature of the coding process, especially for larger datasets, calls for innovative approaches,…

Human-Computer Interaction · Computer Science 2024-03-12 Elisabeth Kirsten , Annalina Buckmann , Abraham Mhaidli , Steffen Becker

We present a parallel approximation algorithm for a class of mixed packing and covering semidefinite programs which generalize on the class of positive semidefinite programs as considered by Jain and Yao [2011]. As a corollary we get a…

Data Structures and Algorithms · Computer Science 2012-01-31 Rahul Jain , Penghui Yao

Linear differential equations are ubiquitous in science and engineering. Quantum computers can simulate quantum systems, which are described by a restricted type of linear differential equations. Here we extend quantum simulation algorithms…

Quantum Physics · Physics 2014-02-21 Dominic W. Berry

This article presents the application of homomorphic authenticators, replication encodings to be precise, to multigroup fully homomorphic encryption schemes. Following the works of Gennaro and Wichs on homomorphic authenticators in…

Cryptography and Security · Computer Science 2023-03-16 Ramsès Fernàndez-València

Random linear network coding is a particularly decentralized approach to the multicast problem. Use of random network codes introduces a non-zero probability however that some sinks will not be able to successfully decode the required…

Information Theory · Computer Science 2007-07-13 Adria Tauste-Campo , Alex Grant

We investigate the problem of recovering coefficients in scalar nonlinear ordinary differential equations that can be exactly linearized. This contribution builds upon prior work by Lyakhov, Gerdt, and Michels, which focused on obtaining a…

Symbolic Computation · Computer Science 2024-04-03 Dmitry A. Lyakhov , Dominik L. Michels

This paper studies a fundamental problem in convex optimization, which is to solve semidefinite programming (SDP) with high accuracy. This paper follows from the existing robust SDP-based interior point method analysis due to [Huang, Jiang,…

Quantum Physics · Physics 2023-02-08 Baihe Huang , Shunhua Jiang , Zhao Song , Runzhou Tao , Ruizhe Zhang

A permutation-invariant code on m qubits is a subspace of the symmetric subspace of the m qubits. We derive permutation-invariant codes that can encode an increasing amount of quantum information while suppressing leading order spontaneous…

Quantum Physics · Physics 2016-05-04 Yingkai Ouyang , Joseph Fitzsimons

A novel decoding algorithm is developed for general quantum convolutional codes. Exploiting useful ideas from classical coding theory, the new decoder introduces two innovations that drastically reduce the decoding complexity compared to…

Quantum Physics · Physics 2015-03-13 Peiyu Tan , Jing Li

We analyze generalizations of quantum algorithms based on the short path framework first proposed by Hastings~[\textit{Quantum} 2, 78 (2018)], which has been extended and shown by Dalzell~et~al.~[STOC~'23] to achieve super-Grover speedups…

Permutation patterns and pattern avoidance have been intensively studied in combinatorics and computer science, going back at least to the seminal work of Knuth on stack-sorting (1968). Perhaps the most natural algorithmic question in this…

Data Structures and Algorithms · Computer Science 2019-04-17 László Kozma

This article describes a very high-level language for clear description of distributed algorithms and optimizations necessary for generating efficient implementations. The language supports high-level control flows where complex…

Programming Languages · Computer Science 2021-10-07 Yanhong A. Liu , Scott D. Stoller , Bo Lin

We present efficient methods to interpolate data with a quantum computer that complement uploading techniques and quantum post-processing. The quantum algorithms are supported by the efficient Quantum Fourier Transform (QFT) and classical…

Quantum Physics · Physics 2023-01-04 Sergi Ramos-Calderer

Large language models (LLMs) have revolutionized natural language processing and broadened their applicability across diverse commercial applications. However, the deployment of these models is constrained by high inference time in…

Computation and Language · Computer Science 2024-11-12 Euiin Yi , Taehyeon Kim , Hongseok Jeung , Du-Seong Chang , Se-Young Yun