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The deletion channel is the simplest point-to-point communication channel that models lack of synchronization. Input bits are deleted independently with probability d, and when they are not deleted, they are not affected by the channel.…

Information Theory · Computer Science 2011-05-02 Yashodhan Kanoria , Andrea Montanari

This paper considers online distributed convex constrained optimization over a time-varying multi-agent network. Agents in this network cooperate to minimize the global objective function through information exchange with their neighbors…

Optimization and Control · Mathematics 2023-05-09 Wentao Zhang , Yang Shi , Baoyong Zhang , Kaihong Lu , Deming Yuan

Every channel can be expressed as a convex combination of deterministic channels with each deterministic channel corresponding to one particular intrinsic state. Such convex combinations are in general not unique, each giving rise to a…

Information Theory · Computer Science 2020-04-28 Shengtian Yang , Rui Xu , Jun Chen , Jian-Kang Zhang

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and…

Systems and Control · Electrical Eng. & Systems 2023-09-12 Apostolos I. Rikos , Wei Jiang , Themistoklis Charalambous , Karl H. Johansson

Tight lower and upper bounds on the ratio of relative entropies of two probability distributions with respect to a common third one are established, where the three distributions are collinear in the standard $(n-1)$-simplex. These bounds…

Information Theory · Computer Science 2018-05-31 Shengtian Yang , Jun Chen

The frequency-domain data of a multivariable system in different operating points is used to design a robust controller with respect to the measurement noise and multimodel uncertainty. The controller is fully parametrized in terms of…

Optimization and Control · Mathematics 2017-08-10 Alireza Karimi , Christoph Kammer

We investigate the limits of communication over the discrete-time Additive White Gaussian Noise (AWGN) channel, when the channel output is quantized using a small number of bits. We first provide a proof of our recent conjecture on the…

Information Theory · Computer Science 2008-05-15 Jaspreet Singh , Onkar Dabeer , Upamanyu Madhow

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability…

Probability · Mathematics 2020-07-03 Mrinal Kanti Roychowdhury , Wasiela Salinas

Performance analysis of optimal signal detection using quantized received signals of a linear vector channel, which is an extension of code-division multiple-access (CDMA) or multiple-input multiple-output (MIMO) channels, in the large…

Information Theory · Computer Science 2008-05-23 Kazutaka Nakamura

In this paper, Gaussian two-way channel with uniform output quantization is studied. For Gaussian inputs, the optimum uniform finite-level quantizer is determined numerically for different values of Signal-to-Noise Ratio (SNR). The two-way…

Information Theory · Computer Science 2016-05-04 Ershad Banijamali

Distributed optimization requires nodes to coordinate, yet full synchronization scales poorly. When $n$ nodes collaborate through $m$ pairwise regularizers, standard methods demand $\mathcal{O}(m)$ communications per iteration. This paper…

Machine Learning · Computer Science 2025-09-19 Ying Lin , Yao Kuang , Ahmet Alacaoglu , Michael P. Friedlander

This paper considers a sequential estimation and sensor scheduling problem with one sensor and one estimator. The sensor makes sequential observations about the state of an underlying memoryless stochastic process, and makes a decision as…

Systems and Control · Computer Science 2016-11-17 Xiaobin Gao , Emrah Akyol , Tamer Basar

In high-dimensional regression, we attempt to estimate a parameter vector $\beta_0\in\mathbb{R}^p$ from $n\lesssim p$ observations $\{(y_i,x_i)\}_{i\leq n}$ where $x_i\in\mathbb{R}^p$ is a vector of predictors and $y_i$ is a response…

Statistics Theory · Mathematics 2022-02-08 Michael Celentano , Andrea Montanari

The goal of a denoising algorithm is to reconstruct a signal from its noise-corrupted observations. Perfect reconstruction is seldom possible and performance is measured under a given fidelity criterion. In a recent work, the authors…

Information Theory · Computer Science 2009-11-11 George Gemelos , Styrmir Sigurjonsson , Tsachy Weissman

In the Naive Bayes classification model the class conditional densities are estimated as the products of their marginal densities along the cardinal basis directions. We study the problem of obtaining an alternative basis for this…

Machine Learning · Statistics 2025-08-19 David P. Hofmeyr , Francois Kamper , Michail C. Melonas

Quantization for probability distributions concerns the best approximation of a $d$-dimensional probability distribution $P$ by a discrete probability with a given number $n$ of supporting points. In this paper, we have considered a…

Dynamical Systems · Mathematics 2022-05-17 Lakshmi Roychowdhury , Mrinal Kanti Roychowdhury

We ask whether the optimal probe is entangled, and if so, what is its character and amount, for estimating the noise parameter of a large class of local quantum encoding processes that we refer to as vector encoding, examples of which…

Quantum Physics · Physics 2026-04-23 Shuva Mondal , Priya Ghosh , Ujjwal Sen

We consider the problem of source coding subject to a fidelity criterion for the Gray-Wyner network that connects a single source with two receivers via a common channel and two private channels. The pareto-optimal trade-offs between the…

Information Theory · Computer Science 2020-10-01 Erixhen Sula , Michael Gastpar

Consider the problem of estimating a random variable $X$ from noisy observations $Y = X+ Z$, where $Z$ is standard normal, under the $L^1$ fidelity criterion. It is well known that the optimal Bayesian estimator in this setting is the…

Statistics Theory · Mathematics 2024-08-08 Leighton P. Barnes , Alex Dytso , Jingbo Liu , H. Vincent Poor

We analyze the effect of squeezing the channel in binary communication based on Gaussian states. We show that for coding on pure states, squeezing increases the detection probability at fixed size of the strategy, actually saturating the…

Quantum Physics · Physics 2009-11-07 Matteo G. A. Paris