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相关论文: Some Comments on the Strong Simplex Conjecture

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The Standard Simplex Conjecture and the Plurality is Stablest Conjecture are two conjectures stating that certain partitions are optimal with respect to Gaussian and discrete noise stability respectively. These two conjectures are natural…

概率论 · 数学 2014-07-10 Steven Heilman , Elchanan Mossel , Joe Neeman

A lower bound on the probability of decoding error of quantum communication channel is presented. The strong converse to the quantum channel coding theorem is shown immediately from the lower bound. It is the same as Arimoto's method exept…

量子物理 · 物理学 2016-11-17 Tomohiro Ogawa , Hiroshi Nagaoka

In this paper, we consider the problem of detecting signals in multiple, sequentially observed data streams. For each stream, the exact distribution is unknown, but characterized by a parameter that takes values in either of two disjoint…

统计方法学 · 统计学 2025-07-30 Yiming Xing , Anamitra Chaudhuri , Yifan Chen

We present an information theoretic proof of the nonsignalling multiprover parallel repetition theorem, a recent extension of its two-prover variant that underlies many hardness of approximation results. The original proofs used de Finetti…

信息论 · 计算机科学 2019-02-01 Himanshu Tyagi , Shun Watanabe

In their seminal work, Bennett et al. [IEEE Trans. Inf. Theory (2002)] showed that, with sufficient shared randomness, one noisy channel can simulate another at a rate equal to the ratio of their capacities. We establish that when coding…

量子物理 · 物理学 2025-09-19 Aadil Oufkir , Yongsheng Yao , Mario Berta

A conjecture of Hopkins (2018) posits that for certain high-dimensional hypothesis testing problems, no polynomial-time algorithm can outperform so-called "simple statistics", which are low-degree polynomials in the data. This conjecture…

计算复杂性 · 计算机科学 2020-04-21 Justin Holmgren , Alexander S. Wein

The performance of ``typical set (pairs) decoding'' for ensembles of Gallager's linear code is investigated using statistical physics. In this decoding, error happens when the information transmission is corrupted by an untypical noise or…

无序系统与神经网络 · 物理学 2009-11-07 Yoshiyuki Kabashima , Kazutaka Nakamura , Jort van Mourik

Based on the numerical representations by T basic vectors of a symbolic sequence consisting of T symbols, first, we prove mathematical that the total Fourier spectrum of the sequence is the square of the length of the sequence. In the…

离散数学 · 计算机科学 2013-10-21 Jiasong Wang , Chuangyin Dang , Changchuan Yin

Counterfactual explanations describe how to modify a feature vector in order to flip the outcome of a trained classifier. Obtaining robust counterfactual explanations is essential to provide valid algorithmic recourse and meaningful…

机器学习 · 计算机科学 2024-03-22 Alexandre Forel , Axel Parmentier , Thibaut Vidal

A generalised concept of the signal-to-noise ratio (or equivalently the ratio of predictable components, or RPC) is provided, based on proper scoring rules. This definition is the natural generalisation of the classical RPC, yet it allows…

应用统计 · 统计学 2026-03-31 Jochen Bröcker , Eviatar Bach

Separating signals from an additive mixture may be an unnecessarily hard problem when one is only interested in specific properties of a given signal. In this work, we tackle simpler "statistical component separation" problems that focus on…

机器学习 · 统计学 2024-03-01 Bruno Régaldo-Saint Blancard , Michael Eickenberg

The explanations of large language models have recently been shown to be sensitive to the randomness used for their training, creating a need to characterize this sensitivity. In this paper, we propose a characterization that questions the…

计算与语言 · 计算机科学 2024-03-18 Jeremie Bogaert , Francois-Xavier Standaert

The Gapeev-Shiryaev conjecture (originating in Gapeev and Shiryaev (2011) and Gapeev and Shiryaev (2013)) can be broadly stated as follows: Monotonicity of the signal-to-noise ratio implies monotonicity of the optimal stopping boundaries.…

概率论 · 数学 2024-05-06 Philip A. Ernst , Goran Peskir

The paper analyzes four classical signal-plus-noise models: the factor model, spiked sample covariance matrices, the sum of a Wigner matrix and a low-rank perturbation, and canonical correlation analysis with low-rank dependencies. The…

统计方法学 · 统计学 2026-02-04 Anna Bykhovskaya , Vadim Gorin , Sasha Sodin

In this work we analyze a convex-programming method for estimating superpositions of point sources or spikes from nonuniform samples of their convolution with a known kernel. We consider a one-dimensional model where the kernel is either a…

最优化与控制 · 数学 2018-06-04 Brett Bernstein , Carlos Fernandez-Granda

We consider the transmission of a memoryless bivariate Gaussian source over an average-power-constrained one-to-two Gaussian broadcast channel. The transmitter observes the source and describes it to the two receivers by means of an…

信息论 · 计算机科学 2009-03-20 Shraga Bross , Amos Lapidoth , Stephan Tinguely

This paper considers the comparison of noisy channels from the viewpoint of statistical decision theory. Various orderings are discussed, all formalizing the idea that one channel is "better" than another for information transmission. The…

信息论 · 计算机科学 2018-03-09 Francesco Buscemi

This paper strengthens the interpretation and understanding of the classical capacity of the pure-loss bosonic channel, first established in [Giovannetti et al., Physical Review Letters 92, 027902 (2004), arXiv:quant-ph/0308012]. In…

量子物理 · 物理学 2014-07-22 Mark M. Wilde , Andreas Winter

The signal demixing problem seeks to separate a superposition of multiple signals into its constituent components. This paper studies a two-stage approach that first decompresses and subsequently deconvolves the noisy and undersampled…

信息检索 · 计算机科学 2022-05-25 Zhenan Fan , Halyun Jeong , Babhru Joshi , Michael P. Friedlander

Noise is an important factor that influences the reliability of information acquisition, transmission, processing, and storage. In order to suppress the inevitable noise effects, a fault-tolerant information processing approach via quantum…

量子物理 · 物理学 2026-03-27 Qi Song , Hongjing Li , Chengxi Yu , Jingzheng Huang , Ding Wang , Peng Huang , Guihua Zeng
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