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In this paper we introduce a fundamental principle for optimal communication over general memoryless channels in the presence of noiseless feedback, termed posterior matching. Using this principle, we devise a (simple, sequential) generic…

信息论 · 计算机科学 2010-08-11 Ofer Shayevitz , Meir Feder

The posterior matching scheme, for feedback encoding of a message point lying on the unit interval over memoryless channels, maximizes mutual information for an arbitrary number of channel uses. However, it in general does not always…

信息论 · 计算机科学 2019-01-10 Diego A. Mesa , Rui Ma , Siva K. Gorantla , Todd P. Coleman

Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution and the Bayesian posterior. Such an approximation leads to severe mode collapse and…

计算机视觉与模式识别 · 计算机科学 2026-05-26 Weimin Bai , Yuxuan Gu , Yifei Wang , Weijian Luo , He Sun

The partial monitoring (PM) framework provides a theoretical formulation of sequential learning problems with incomplete feedback. On each round, a learning agent plays an action while the environment simultaneously chooses an outcome. The…

机器学习 · 计算机科学 2024-05-17 Maxime Heuillet , Ola Ahmad , Audrey Durand

We recently showed in [1] the superiority of certain structured coding matrices ensembles (such as partial row-orthogonal) for sparse superposition codes when compared with purely random matrices with i.i.d. entries, both…

信息论 · 计算机科学 2022-07-12 YuHao Liu , Teng Fu , Jean Barbier , TianQi Hou

This paper introduces posterior mean matching (PMM), a new method for generative modeling that is grounded in Bayesian inference. PMM uses conjugate pairs of distributions to model complex data of various modalities like images and text,…

机器学习 · 计算机科学 2024-12-23 Sebastian Salazar , Michal Kucer , Yixin Wang , Emily Casleton , David Blei

Bayesian methods are appealing in their flexibility in modeling complex data and ability in capturing uncertainty in parameters. However, when Bayes' rule does not result in tractable closed-form, most approximate inference algorithms lack…

机器学习 · 计算机科学 2016-05-09 Bo Dai , Niao He , Hanjun Dai , Le Song

Existing fixed-length feedback communication schemes are either specialized to particular channels (Schalkwijk--Kailath, Horstein), or apply to general channels but either have high coding complexity (block feedback schemes) or are…

信息论 · 计算机科学 2016-09-08 Cheuk Ting Li , Abbas El Gamal

We consider the problem of communication over the binary symmetric channel with feedback, where the information sequence is made available in a causal, possibly random, fashion. We develop a real-time variant of the renowned Horstein scheme…

信息论 · 计算机科学 2020-12-08 Anusha Lalitha , Anatoly Khina , Tara Javidi

We propose simple randomized strategies for sequential prediction under imperfect monitoring, that is, when the forecaster does not have access to the past outcomes but rather to a feedback signal. The proposed strategies are consistent in…

统计理论 · 数学 2008-01-07 Gabor Lugosi , Shie Mannor , Gilles Stoltz

The Pseudo-Marginal (PM) algorithm is a popular Markov chain Monte Carlo (MCMC) method used to sample from a target distribution when its density is inaccessible, but can be estimated with a non-negative unbiased estimator. Its performance…

统计计算 · 统计学 2025-09-30 Sarra Abaoubida , Mylène Bédard , Florian Maire

Posterior matching is a method proposed by Ofer Shayevitz and Meir Feder to design capacity achieving coding schemes for general point-to-point memoryless channels with feedback. In this paper, we present a way to extend posterior matching…

信息论 · 计算机科学 2016-11-17 Lan V. Truong

We study variable-length feedback (VLF) codes over binary-input memoryless symmetric (BMS) channels using posterior matching with small-enough-difference (SED) partitioning. Prior analyses of SED-based schemes rely on bounded log-likelihood…

信息论 · 计算机科学 2026-04-06 Recep Can Yavas

The performance of Maximum a posteriori (MAP) estimation is studied analytically for binary symmetric multi-channel Hidden Markov processes. We reduce the estimation problem to a 1D Ising spin model and define order parameters that…

统计力学 · 物理学 2015-06-11 Avik Halder , Ansuman Adhikary

Iterative thresholding algorithms are well-suited for high-dimensional problems in sparse recovery and compressive sensing. The performance of this class of algorithms depends heavily on the tuning of certain threshold parameters. In…

信息论 · 计算机科学 2013-11-04 Ali Mousavi , Arian Maleki , Richard G. Baraniuk

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

信息论 · 计算机科学 2016-11-15 Zheng Wang , Jie Luo

We present a new algorithm based on posterior sampling for learning in constrained Markov decision processes (CMDP) in the infinite-horizon undiscounted setting. The algorithm achieves near-optimal regret bounds while being advantageous…

机器学习 · 计算机科学 2023-09-28 Danil Provodin , Pratik Gajane , Mykola Pechenizkiy , Maurits Kaptein

Recovering a signal from its degraded measurements is a long standing challenge in science and engineering. Recently, zero-shot diffusion based methods have been proposed for such inverse problems, offering a posterior sampling based…

机器学习 · 计算机科学 2026-05-19 Roi Benita , Michael Elad , Joseph Keshet

In this paper, the posterior matching scheme proposed by Shayevits and Feder is extended to the Gaussian broadcast channel with feedback, and the error probabilities and achievable rate region are derived for this coding strategy by using…

信息论 · 计算机科学 2019-04-09 Lan V. Truong , Hirosuke Yamamoto

Motivated by recent work on entanglement-assisted codes for sending messages over classical channels, the larger, easily characterised class of non-signalling codes is defined. Analysing the optimal performance of these codes yields an…

量子物理 · 物理学 2016-01-01 William Matthews
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