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Let (S1,i, S2,i), distributed according to i.i.d p(s1, s2), i = 1, 2, . . . be a memoryless, correlated partial side information sequence. In this work we study channel coding and source coding problems where the partial side information…

Information Theory · Computer Science 2013-04-12 Avihay Shirazi , Uria Basher , Haim Permuter

We derive information-theoretic lower bounds on the Bayes risk and generalization error of realizable machine learning models. In particular, we employ an analysis in which the rate-distortion function of the model parameters bounds the…

Machine Learning · Computer Science 2021-11-09 Matthew Nokleby , Ahmad Beirami

Recovery of the sparsity pattern (or support) of an unknown sparse vector from a limited number of noisy linear measurements is an important problem in compressed sensing. In the high-dimensional setting, it is known that recovery with a…

Information Theory · Computer Science 2012-06-26 Galen Reeves , Michael Gastpar

We calculate the large deviations for the length of the longest alternating subsequence and for the length of the longest increasing subsequence in a uniformly random permutation that avoids a pattern of length three. We treat all six…

Probability · Mathematics 2023-09-04 Ross G. Pinsky

In this paper, we analyze the indirect source coding problem with side information at both the encoder and decoder, as well as only at the decoder. We first derive structural properties of the two rate distortion functions (RDFs) for…

Information Theory · Computer Science 2024-10-14 Evagoras Stylianou , Michail Gkagkos , Charalambos D. Charalambous

This paper provides lower bounds on the reconstruction error for transmission of two continuous correlated random vectors sent over both sum and parallel channels using the help of two causal feedback links from the decoder to the encoders…

Information Theory · Computer Science 2013-08-16 Ayşe Ünsal , Raymond Knopp

A simple lower bound to the capacity of the discrete-time Poisson channel with average energy $\es$ is derived. The rate ${1/2}\log(1+\es)$ is shown to be the generalized mutual information of a modified minimum-distance decoder, when the…

Information Theory · Computer Science 2008-09-22 Alfonso Martinez

A secrecy system with side information at the decoders is studied in the context of lossy source compression over a noiseless broadcast channel. The decoders have access to different side information sequences that are correlated with the…

Information Theory · Computer Science 2014-10-07 Eva C. Song , Paul Cuff , H. Vincent Poor

In lossy compression, Blau and Michaeli [5] introduced the information rate-distortion-perception (RDP) function, extending traditional rate-distortion theory by incorporating perceptual quality. More recently, this framework was expanded…

Information Theory · Computer Science 2025-04-15 Nam Nguyen , Thinh Nguyen , Bella Bose

Minimum power required to achieve a distortion-noise profile, i.e., a function indicating the maximum allowed distortion value for each noise level, is studied for the transmission of Gaussian sources over Gaussian channels under a regime…

Information Theory · Computer Science 2020-01-22 Mohammadamin Baniasadi , Ertem Tuncel

The article starts with new aliasing-truncation error upper bounds in the sampling theorem for non-bandlimited stochastic signals. Then, it investigates $L_p([0,T])$ approximations of sub-Gaussian random signals. Explicit truncation error…

Information Theory · Computer Science 2016-08-15 Yuriy Kozachenko , Andriy Olenko

This paper studies the minimum achievable source coding rate as a function of blocklength $n$ and probability $\epsilon$ that the distortion exceeds a given level $d$. Tight general achievability and converse bounds are derived that hold at…

Information Theory · Computer Science 2016-11-15 Victoria Kostina , Sergio Verdú

This paper studies a class of stochastic and time-varying Gaussian intersymbol interference~(ISI) channels. The probability law for the~$i^{th}$ channel tap during time slot~$t$ is supported over an interval of centre $c_i$ and radius~$…

Information Theory · Computer Science 2022-08-16 Kamyar Moshksar

A fundamental question in designing lossy data compression schemes is how well one can do in comparison with the rate-distortion function, which describes the known theoretical limits of lossy compression. Motivated by the empirical success…

Information Theory · Computer Science 2024-03-05 Eric Lei , Hamed Hassani , Shirin Saeedi Bidokhti

We present a sparse analogue to stochastic gradient descent that is guaranteed to perform well under similar conditions to the lasso. In the linear regression setup with irrepresentable noise features, our algorithm recovers the support set…

Statistics Theory · Mathematics 2014-12-16 Jacob Steinhardt , Stefan Wager , Percy Liang

A general expression for the distortion rate function (DRF) of cyclostationary Gaussian processes in terms of their spectral properties is derived. This expression can be seen as the result of orthogonalization over the different components…

Information Theory · Computer Science 2016-08-11 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar

We consider a novel variant of $d$-semifaithful lossy coding in which the distortion measure is revealed only to the encoder and only at run-time, as well as an extension of it in which the distortion constraint $d$ is also revealed at…

Information Theory · Computer Science 2022-10-05 Adeel Mahmood , Aaron B. Wagner

A bifurcating system subject to multiplicative noise can exhibit on-off intermittency close to the instability threshold. For a canonical system, we discuss the dependence of this intermittency on the Power Spectrum Density (PSD) of the…

Statistical Mechanics · Physics 2015-05-13 Sebastien Aumaitre , Kirone Mallick , Francois Petrelis

We consider approximations of signals by the elements of a frame in a complex vector space of dimension $N$ and formulate both the noiseless and the noisy sparse representation problems. The noiseless representation problem is to find…

Information Theory · Computer Science 2007-07-13 Mehmet Akçakaya , Vahid Tarokh

The rate-distortion-perception function (RDPF; Blau and Michaeli, 2019) has emerged as a useful tool for thinking about realism and distortion of reconstructions in lossy compression. Unlike the rate-distortion function, however, it is…

Information Theory · Computer Science 2021-04-29 Lucas Theis , Aaron B. Wagner