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Modern program verifiers use logic-based encodings of the verification problem that are discharged by a back end reasoning engine. However, instances of such encodings for large programs can quickly overwhelm these back end solvers. Hence,…

Logic in Computer Science · Computer Science 2016-07-18 Peter Schrammel

In this paper, we use reinforcement learning to find effective decoding strategies for binary linear codes. We start by reviewing several iterative decoding algorithms that involve a decision-making process at each step, including…

Information Theory · Computer Science 2019-12-10 Fabrizio Carpi , Christian Häger , Marco Martalò , Riccardo Raheli , Henry D. Pfister

Departing from traditional communication theory where decoding algorithms are assumed to perform without error, a system where noise perturbs both computational devices and communication channels is considered here. This paper studies…

Information Theory · Computer Science 2010-05-31 Lav R. Varshney

Cooperative optimization is a new way for finding global optima of complicated functions of many variables. It has some important properties not possessed by any conventional optimization methods. It has been successfully applied in solving…

Information Theory · Computer Science 2007-07-13 Xiaofei Huang

A lower bound on the maximum likelihood (ML) decoding error exponent of linear block code ensembles, on the erasure channel, is developed. The lower bound turns to be positive, over an ensemble specific interval of erasure probabilities,…

Information Theory · Computer Science 2019-01-23 Enrico Paolini , Gianluigi Liva

We consider a decoder with an erasure option and a variable size list decoder for channels with non-casual side information at the transmitter. First, universally achievable error exponents are offered for decoding with an erasure option…

Information Theory · Computer Science 2009-03-13 Erez Sabbag , Neri Merhav

Network coding is a highly efficient data dissemination mechanism for wireless networks. Since network coded information can only be recovered after delivering a sufficient number of coded packets, the resulting decoding delay can become…

Information Theory · Computer Science 2016-11-17 Rui A. Costa , Daniele Munaretto , Joerg Widmer , Joao Barros

The problem of channel coding with the erasure option is revisited for discrete memoryless channels. The interplay between the code rate, the undetected and total error probabilities is characterized. Using the information spectrum method,…

Information Theory · Computer Science 2015-10-22 Masahito Hayashi , Vincent Y. F. Tan

For polar codes, successive cancellation list (SCL) decoding algorithm significantly improves finite-length performance compared to SC decoding. SCL-flip decoding can further enhance the performance but the gain diminishes as code length…

Information Theory · Computer Science 2024-07-08 Xianbin Wang , Huazi Zhang , Jiajie Tong , Jun Wang , Wen Tong

A complexity-adaptive tree search algorithm is proposed for $\boldsymbol{G}_N$-coset codes that implements maximum-likelihood (ML) decoding by using a successive decoding schedule. The average complexity is close to that of the successive…

Information Theory · Computer Science 2021-09-03 Peihong Yuan , Mustafa Cemil Coşkun

In a recent paper ([1]=quant-ph/0606035) it is shown how the optimal recovery operation in an error correction scheme can be considered as a semidefinite program. As a possible future improvement it is noted that still better error…

Quantum Physics · Physics 2007-05-23 M. Reimpell , R. F. Werner , K. Audenaert

Long polar codes can achieve the capacity of arbitrary binary-input discrete memoryless channels under a low complexity successive cancelation (SC) decoding algorithm. But for polar codes with short and moderate code length, the decoding…

Information Theory · Computer Science 2016-11-18 Jun Lin , Chenrong Xiong , Zhiyuan Yan

The wiretap channel is a well-studied problem in the physical layer security literature. Although it is proven that the decoding error probability and information leakage can be made arbitrarily small in the asymptotic regime, further…

Information Theory · Computer Science 2025-03-19 Daniel Seifert , Onur Günlü , Rafael F. Schaefer

This paper studies maximum likelihood(ML) decoding in error-correcting codes as rational maps and proposes an approximate ML decoding rule by using a Taylor expansion. The point for the Taylor expansion, which will be denoted by $p$ in the…

Dynamical Systems · Mathematics 2010-06-30 Kazunori Hayashi , Yasuaki Hiraoka

Since the classical work of Berlekamp, McEliece and van Tilborg, it is well known that the problem of exact maximum-likelihood (ML) decoding of general linear codes is NP-hard. In this paper, we show that exact ML decoding of a classs of…

Information Theory · Computer Science 2016-11-17 Weiyu Xu , Babak Hassibi

Polar codes are the first class of constructive channel codes achieving the symmetric capacity of the binary-input discrete memoryless channels. But the analysis and construction of polar codes involve the complex iterative-calculation. In…

Information Theory · Computer Science 2019-11-26 Kai Niu , Yan Li , Weiling Wu

We consider the problem of erasure/list decoding using certain classes of simplified decoders. Specifically, we assume a class of erasure/list decoders, such that a codeword is in the list if its likelihood is larger than a threshold. This…

Information Theory · Computer Science 2016-11-17 Nir Weinberger , Neri Merhav

Constrained sequence codes have been widely used in modern communication and data storage systems. Sequences encoded with constrained sequence codes satisfy constraints imposed by the physical channel, hence enabling efficient and reliable…

Information Theory · Computer Science 2018-09-07 Congzhe Cao , Duanshun Li , Ivan Fair

We construct efficient data structures that are resilient against a constant fraction of adversarial noise. Our model requires that the decoder answers most queries correctly with high probability and for the remaining queries, the decoder…

Data Structures and Algorithms · Computer Science 2010-01-27 Victor Chen , Elena Grigorescu , Ronald de Wolf

In spite of the great potential of large language models (LLMs) across various tasks, their deployment on resource-constrained devices remains challenging due to their excessive computational and memory demands. Quantization has emerged as…

Machine Learning · Computer Science 2025-02-28 Hao Mark Chen , Fuwen Tan , Alexandros Kouris , Royson Lee , Hongxiang Fan , Stylianos I. Venieris