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Logistic regression is one of the most popular methods in binary classification, wherein estimation of model parameters is carried out by solving the maximum likelihood (ML) optimization problem, and the ML estimator is defined to be the…

Optimization and Control · Mathematics 2018-10-23 Robert M. Freund , Paul Grigas , Rahul Mazumder

The statistical physics properties of low-density parity-check codes for the binary symmetric channel are investigated as a spin glass problem with multi-spin interactions and quenched random fields by the cavity method. By evaluating the…

Statistical Mechanics · Physics 2015-01-20 Haiping Huang

Noise and errors are unavoidable in any realistic quantum process, including processes designed to reduce noise and errors in the first place. In particular, quantum thermodynamical protocols for cooling can be significantly affected,…

Quantum Physics · Physics 2026-01-26 Jian Li , Xiaoyang Wang , Marcus Huber , Nicolai Friis , Pharnam Bakhshinezhad

Fault-tolerant quantum computers use decoders to monitor for errors and find a plausible correction. A decoder may provide a decoder confidence score (DCS) to gauge its success. We adopt a swim distance DCS, computed from the shortest path…

Quantum Physics · Physics 2026-01-19 Maria Dincă , Tim Chan , Simon C. Benjamin

In this paper, the proximal decoding algorithm is considered within the context of additive white Gaussian noise (AWGN) channels. An analysis of the convergence behavior of the algorithm shows that proximal decoding inherently enters an…

Information Theory · Computer Science 2024-09-12 Andreas Tsouchlos , Holger Jäkel , Laurent Schmalen

The performance of an error correcting code is evaluated by its error probability, rate, and en/decoding complexity. The performance of a series of codes is evaluated by, as the block lengths approach infinity, whether their error…

Information Theory · Computer Science 2021-07-15 Hsin-Po Wang

We are motivated by problems that arise in a number of applications such as Online Marketing and Explosives detection, where the observations are usually modeled using Poisson statistics. We model each observation as a Poisson random…

Machine Learning · Statistics 2016-06-29 Mohammad H. Rohban , Delaram Motamedvaziri , Venkatesh Saligrama

In this work, we develop an efficient decoding method for graph codes, a class of stabilizer quantum error-correcting codes constructed from graph states. While optimal decoding is generally NP-hard, we propose a faster decoder exploiting…

Quantum Physics · Physics 2026-02-17 Nirupam Basak , Goutam Paul

This paper studies the problem of reconstructing a word given several of its noisy copies. This setup is motivated by several applications, among them is reconstructing strands in DNA-based storage systems. Under this paradigm, a word is…

Information Theory · Computer Science 2020-01-17 Omer Sabary , Eitan Yaakobi , Alexander Yucovich

The min-sum approximation is widely used in the decoding of polar codes. Although it is a numerical approximation, hardly any penalties are incurred in practice. We give a theoretical justification for this. We consider the common case of a…

Information Theory · Computer Science 2025-03-04 Nir Chisnevski , Ido Tal , Shlomo Shamai

Systematic polar codes are shown to outperform non-systematic polar codes in terms of the bit-error-rate (BER) performance. However theoretically the mechanism behind the better performance of systematic polar codes is not yet clear. In…

Information Theory · Computer Science 2015-04-17 Liping Li , Wenyi Zhang , Yanjun Hu

For semantic segmentation, label probabilities are often uncalibrated as they are typically only the by-product of a segmentation task. Intersection over Union (IoU) and Dice score are often used as criteria for segmentation success, while…

Computer Vision and Pattern Recognition · Computer Science 2021-07-28 Zhipeng Ding , Xu Han , Peirong Liu , Marc Niethammer

Topological quantum error-correcting codes are a promising candidate for building fault-tolerant quantum computers. Decoding topological codes optimally, however, is known to be a computationally hard problem. Various decoders have been…

Quantum Physics · Physics 2020-04-01 Milap Sheth , Sara Zafar Jafarzadeh , Vlad Gheorghiu

The noise model of deletions poses significant challenges in coding theory, with basic questions like the capacity of the binary deletion channel still being open. In this paper, we study the harder model of worst-case deletions, with a…

Information Theory · Computer Science 2014-11-26 Venkatesan Guruswami , Carol Wang

Fracton models provide examples of novel gapped quantum phases of matter that host intrinsically immobile excitations and therefore lie beyond the conventional notion of topological order. Here, we calculate optimal error thresholds for…

Quantum Physics · Physics 2022-12-06 Hao Song , Janik Schönmeier-Kromer , Ke Liu , Oscar Viyuela , Lode Pollet , M. A. Martin-Delgado

We consider the problem of computing a binary linear transformation using unreliable components when all circuit components are unreliable. Two noise models of unreliable components are considered: probabilistic errors and permanent errors.…

Information Theory · Computer Science 2017-05-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering…

Information Theory · Computer Science 2016-04-07 Eva C. Song , Paul Cuff , H. Vincent Poor

In this paper we show a polar coding scheme for the deletion channel with a probability of error that decays roughly like $2^{-\sqrt{\Lambda}}$, where $\Lambda$ is the length of the codeword. That is, the same decay rate as that of seminal…

Information Theory · Computer Science 2024-10-24 Dar Arava , Ido Tal

A new score function is proposed for stack decoding of polar codes, which enables one to accurately compare paths of different lengths. The proposed score function includes bias, which reflects the average behaviour of the correct path.…

Information Theory · Computer Science 2018-01-16 Peter Trifonov , Vera Miloslavskaya , Ruslan Morozov

We study approximations of the partition function of dense graphical models. Partition functions of graphical models play a fundamental role is statistical physics, in statistics and in machine learning. Two of the main methods for…

Machine Learning · Computer Science 2018-02-21 Vishesh Jain , Frederic Koehler , Elchanan Mossel