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We consider implementations of a bipartite unitary on many pairs of unknown input states by local operation and classical communication assisted by shared entanglement. We investigate to what extent the entanglement cost and the classical…

Quantum Physics · Physics 2014-07-21 Eyuri Wakakuwa , Mio Murao

We study the effect that the amount of correlation in a bipartite distribution has on the communication complexity of a problem under that distribution. We introduce a new family of complexity measures that interpolates between the two…

Computational Complexity · Computer Science 2015-08-25 Ralph C. Bottesch , Dmitry Gavinsky , Hartmut Klauck

The minimum energy, and, more generally, the minimum cost, to transmit one bit of information has been recently derived for bursty communication when information is available infrequently at random times at the transmitter. Furthermore, it…

Information Theory · Computer Science 2017-10-25 Venkat Chandar , Aslan Tchamkerten

A new framework is introduced for examining and evaluating the fundamental limits of lossless data compression, that emphasizes genuinely non-asymptotic results. The {\em sample complexity} of compressing a given source is defined as the…

Information Theory · Computer Science 2026-04-16 Terence Viaud , Ioannis Kontoyiannis

We study the relative entropy between the empirical estimate of a discrete distribution and the true underlying distribution. If the minimum value of the probability mass function exceeds an $\alpha > 0$ (i.e. when the true underlying…

Statistics Theory · Mathematics 2021-09-21 Alankrita Bhatt , Ankit Pensia

This paper shows the strong converse and the dispersion of memoryless channels with cost constraints and performs refined analysis of the third order term in the asymptotic expansion of the maximum achievable channel coding rate, showing…

Information Theory · Computer Science 2015-10-09 Victoria Kostina , Sergio Verdú

Estimating divergences in a consistent way is of great importance in many machine learning tasks. Although this is a fundamental problem in nonparametric statistics, to the best of our knowledge there has been no finite sample exponential…

Information Theory · Computer Science 2016-03-30 Shashank Singh , Barnabás Póczos

This paper provides tight bounds on the R\'enyi entropy of a function of a discrete random variable with a finite number of possible values, where the considered function is not one-to-one. To that end, a tight lower bound on the R\'enyi…

Information Theory · Computer Science 2018-12-11 Igal Sason

The parametric complexity is the key quantity in the minimum description length (MDL) approach to statistical model selection. Rissanen and others have shown that the parametric complexity of a statistical model approaches a simple function…

Information Theory · Computer Science 2015-10-30 James G. Dowty

We consider the problem of covert communication with random slot selection over binary-input Discrete Memoryless Channels and Additive White Gaussian Noise channels, in which a transmitter attempts to reliably communicate with a legitimate…

Information Theory · Computer Science 2025-07-21 Shi-Yuan Wang , Keerthi S. K. Arumugam , Matthieu R. Bloch

This paper provides upper and lower bounds on the optimal guessing moments of a random variable taking values on a finite set when side information may be available. These moments quantify the number of guesses required for correctly…

Information Theory · Computer Science 2018-06-22 Igal Sason , Sergio Verdú

The random variable simulation problem consists in using a $k$-dimensional i.i.d. random vector $X^{k}$ with distribution $P_{X}^{k}$ to simulate an $n$-dimensional i.i.d. random vector $Y^{n}$ so that its distribution is approximately…

Information Theory · Computer Science 2018-12-24 Lei Yu , Vincent Y. F. Tan

This study examines sharp bounds on Arimoto's conditional R\'enyi entropy of order $\beta$ with a fixed another one of distinct order $\alpha \neq \beta$. Arimoto inspired the relation between the R\'enyi entropy and the $\ell_{r}$-norm of…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Ken-ichi Iwata

We show lower bounds of $\Omega(\sqrt{n})$ and $\Omega(n^{1/4})$ on the randomized and quantum communication complexity, respectively, of all $n$-variable read-once Boolean formulas. Our results complement the recent lower bound of…

Computational Complexity · Computer Science 2009-09-01 Rahul Jain , Hartmut Klauck , Shengyu Zhang

This dissertation investigates relative entropies, also called generalized divergences, and how they can be used to characterize information-theoretic tasks in quantum information theory. The main goal is to further refine characterizations…

Quantum Physics · Physics 2016-11-29 Felix Leditzky

The conventional channel resolvability problem refers to the determination of the minimum rate required for an input process so that the output distribution approximates a target distribution in either the total variation distance or the…

Information Theory · Computer Science 2018-12-04 Lei Yu , Vincent Y. F. Tan

We consider the randomized communication complexity of the distributed $\ell_p$-regression problem in the coordinator model, for $p\in (0,2]$. In this problem, there is a coordinator and $s$ servers. The $i$-th server receives $A^i\in\{-M,…

Data Structures and Algorithms · Computer Science 2023-07-12 Yi Li , Honghao Lin , David P. Woodruff

This article presents the calculation of the entropy of a system with Zipfian distribution and shows that a communication system tends to present an exponent value close to one, but still greater than one, so that it might maximize entropy…

Applications · Statistics 2013-07-04 Leonardo Carneiro Araujo , Thaïs Cristófaro-Silva , Hani Camille Yehia

We prove an optimal $\Omega(n)$ lower bound on the randomized communication complexity of the much-studied Gap-Hamming-Distance problem. As a consequence, we obtain essentially optimal multi-pass space lower bounds in the data stream model…

Computational Complexity · Computer Science 2012-07-02 Amit Chakrabarti , Oded Regev

This paper establishes the strict optimality in precision for frequency and distribution estimation under local differential privacy (LDP). We prove that a linear estimator with a symmetric and extremal configuration, and a constant support…

Information Theory · Computer Science 2026-03-24 Mingen Pan