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This paper investigates the soft covering lemma under both the relative entropy and the total variation distance as the measures of deviation. The exact order of the expected deviation of the random i.i.d. code for the soft covering problem…

Information Theory · Computer Science 2019-02-22 Mohammad Hossein Yassaee

Real continuous submodular functions, as a generalization of the corresponding discrete notion to the continuous domain, gained considerable attention recently. The analog notion for entropy functions requires additional properties: a real…

Optimization and Control · Mathematics 2021-02-12 Laszlo Csirmaz

We propose that chaotic Glass networks (a class of piecewise-linear Ordinary Differential Equations) are good candidates for the design of true random number generators. A Glass network design has the advantage of involving only standard…

Dynamical Systems · Mathematics 2025-02-14 Benjamin W. Wild , Roderick Edwards

We establish upper and lower bounds for the metric entropy and bracketing entropy of the class of $d$-dimensional bounded monotonic functions under $L^p$ norms. It is interesting to see that both the metric entropy and bracketing entropy…

Statistics Theory · Mathematics 2007-06-13 Fuchang Gao , Jon A. Wellner

In this paper, we study approximation properties of single hidden layer neural networks with weights varying on finitely many directions and thresholds from an open interval. We obtain a necessary and at the same time sufficient measure…

Machine Learning · Computer Science 2023-04-05 Vugar Ismailov , Ekrem Savas

When constructing models of the world, we aim for optimal compressions: models that include as few details as possible while remaining as accurate as possible. But which details -- or features measured in data -- should we choose to include…

Quantitative Methods · Quantitative Biology 2025-05-06 David P. Carcamo , Nicholas J. Weaver , Purushottam D. Dixit , Christopher W. Lynn

The behavior of the Kozachenko - Leonenko estimates for the (differential) Shannon entropy is studied when the number of i.i.d. vector-valued observations tends to infinity. The asymptotic unbiasedness and L^2-consistency of the estimates…

Statistics Theory · Mathematics 2018-01-09 Alexander Bulinski , Denis Dimitrov

In this paper, we present a new multi-scale information content calculation method based on Shannon information (and Shannon entropy). The original method described by Claude E. Shannon and based on the logarithm of the probability of…

Information Theory · Computer Science 2023-05-23 Zsolt Pocze

We present and study approximate notions of dimensional and margin complexity, which correspond to the minimal dimension or norm of an embedding required to approximate, rather then exactly represent, a given hypothesis class. We show that…

Machine Learning · Computer Science 2020-03-10 Pritish Kamath , Omar Montasser , Nathan Srebro

Recent advancements in deep learning-based image compression are notable. However, prevalent schemes that employ a serial context-adaptive entropy model to enhance rate-distortion (R-D) performance are markedly slow. Furthermore, the…

Applications · Statistics 2024-03-25 Haisheng Fu , Feng Liang , Jie Liang , Zhenman Fang , Guohe Zhang , Jingning Han

We construct a new representation of entropy solutions to nonlinear scalar conservation laws with a smooth convex flux function in a single spatial dimension. The representation is a generalization of the method of characteristics and…

Numerical Analysis · Mathematics 2026-01-15 Donsub Rim , Gerrit Welper

In this thesis, we provide an initial investigation into bounds for topological entropy of switched linear systems. Entropy measures, roughly, the information needed to describe the behavior of a system with finite precision on finite time…

Optimization and Control · Mathematics 2016-10-14 James Schmidt

This paper studies the problem of estimating the differential entropy $h(S+Z)$, where $S$ and $Z$ are independent $d$-dimensional random variables with $Z\sim\mathcal{N}(0,\sigma^2 \mathrm{I}_d)$. The distribution of $S$ is unknown, but $n$…

Statistics Theory · Mathematics 2019-06-04 Ziv Goldfeld , Kristjan Greenewald , Yury Polyanskiy

In many sequence learning tasks, such as program synthesis and document summarization, a key problem is searching over a large space of possible output sequences. We propose to learn representations of the outputs that are specifically…

Machine Learning · Computer Science 2021-08-09 Joey Hong , David Dohan , Rishabh Singh , Charles Sutton , Manzil Zaheer

Shannon entropy is a polymatroidal set function and lies at the foundation of information theory, yet the class of entropic polymatroids is strictly smaller than the class of all submodular functions. In parallel, submodular and…

Information Theory · Computer Science 2026-01-21 Rishabh Iyer

Maximal repetition of a string is the maximal length of a repeated substring. This paper investigates maximal repetition of strings drawn from stochastic processes. Strengthening previous results, two new bounds for the almost sure growth…

Information Theory · Computer Science 2020-03-11 Łukasz Dębowski

This work comprises a detailed theoretical and computational study of the boundary value problem for transversely isotropic linear elastic bodies. General conditions for well-posedness are derived in terms of the material parameters. The…

Numerical Analysis · Mathematics 2018-11-01 Faraniaina Rasolofoson , Beverley Grieshaber , B. Daya Reddy

The problem of determining the best achievable performance of arbitrary lossless compression algorithms is examined, when correlated side information is available at both the encoder and decoder. For arbitrary source-side information pairs,…

Information Theory · Computer Science 2020-07-15 Lampros Gavalakis , Ioannis Kontoyiannis

We present a numerical study of the application of the Shannon entropy technique to the planar restricted three-body problem in the vicinity of first-order interior mean-motion resonances with the perturber. We estimate the diffusion…

Chaotic Dynamics · Physics 2020-01-08 C. Beaugé , P. M. Cincotta

Consider the problem of estimating the Shannon entropy of a distribution over $k$ elements from $n$ independent samples. We show that the minimax mean-square error is within universal multiplicative constant factors of $$\Big(\frac{k }{n…

Information Theory · Computer Science 2016-02-19 Yihong Wu , Pengkun Yang