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We establish the Strassen's law of the iterated logarithm for independent and identically distributed random variables with $\hat{\mathbb{E}}[X_1]=\hat{\mathcal{E}}[X_1]=0$ and $C_{\mathbb{V}}[X_1^2]<\infty$ under sub-linear expectation…

Probability · Mathematics 2022-12-22 Wang-yun Gu , Li-xin Zhang

An algorithm is described that enables efficient deterministic approximate computation of the bootstrap distribution for any linear bootstrap method $T_n^*$, alleviating the need for repeated resampling from observations (resp.…

Methodology · Statistics 2019-04-10 Thomas Pitschel

In this paper, we are concerned with regression problems where covariates can be grouped in nonoverlapping blocks, and where only a few of them are assumed to be active. In such a situation, the group Lasso is an at- tractive method for…

Information Theory · Computer Science 2013-01-01 Samuel Vaiter , Charles Deledalle , Gabriel Peyré , Jalal Fadili , Charles Dossal

In this paper we study extensively the discrete logarithm problem in the group of non-singular circulant matrices. The emphasis of this study was to find the exact parameters for the group of circulant matrices for a secure implementation.…

Cryptography and Security · Computer Science 2012-07-06 Ayan Mahalanobis

This talk describes the work done in calculating leading logarithms in massive effective field theories. We discuss shortly leading logarithms in renormalizable theories and how they can be calculated using only one-loop calculations in…

High Energy Physics - Phenomenology · Physics 2015-09-25 Johan Bijnens , Karol Kampf , Alexey Vladimirov

We consider directed random polymers in $(d+1)$ dimensions with nearly gamma i.i.d. disorder. We study the partition function $Z_{N,\omega}$ and establish exponential concentration of $\log Z_{N,\omega}$ about its mean on the subgaussian…

Probability · Mathematics 2013-03-26 Kenneth S. Alexander , Nikos Zygouras

Denoising diffusions are state-of-the-art generative models exhibiting remarkable empirical performance. They work by diffusing the data distribution into a Gaussian distribution and then learning to reverse this noising process to obtain…

Machine Learning · Statistics 2024-02-20 Joe Benton , Yuyang Shi , Valentin De Bortoli , George Deligiannidis , Arnaud Doucet

This article is interested in pullbacks under the logarithmic derivative of algebraic ordinary differential equations. In particular, assuming the solution set of an equation is internal to the constants, we would like to determine when its…

Logic · Mathematics 2025-03-20 Christine Eagles , Léo Jimenez

Generalized non-autonomous linear celullar automata are systems of linear difference equations with many variables that can be seen as convolution equations in a discrete group. We study those systems from the stand point of the Galois…

Dynamical Systems · Mathematics 2013-08-07 David Blazquez-Sanz , Weimar Muñoz

In this work, we propose and investigate stable high-order collocation-type discretisations of the discontinuous Galerkin method on equidistant and scattered collocation points. We do so by incorporating the concept of discrete least…

Numerical Analysis · Mathematics 2021-02-24 Jan Glaubitz , Philipp Oeffner

In this paper, an alternative Discrete skew Logistic distribution is proposed, which is derived by using the general approach of discretizing a continuous distribution while retaining its survival function. The properties of the…

Methodology · Statistics 2016-04-07 Deepesh Bhati , Subrata Chakraborty , Snober Gowhar Lateef

We briefly review two different methods of applying Lie group theory in the numerical solution of ordinary differential equations. On specific examples we show how the symmetry preserving discretization provides difference schemes for which…

Mathematical Physics · Physics 2013-04-29 Decio Levi , Pavel Winternitz

For an arbitrary initial configuration of discrete loads over vertices of a distributed graph, we consider the problem of minimizing the {\em discrepancy} between the maximum and minimum loads among all vertices. For this problem, this…

Data Structures and Algorithms · Computer Science 2018-05-15 Takeharu Shiraga

We develop generalization error bounds for stochastic gradient descent (SGD) with label noise in non-convex settings under uniform dissipativity and smoothness conditions. Under a suitable choice of semimetric, we establish a contraction in…

Machine Learning · Statistics 2023-11-02 Jung Eun Huh , Patrick Rebeschini

Differentially private mechanisms are increasingly used to publish tables of counts, where each entry represents the number of individuals belonging to a particular category. A distribution of counts summarizes the information in the count…

Cryptography and Security · Computer Science 2026-04-03 Nitin Kohli , Paul Laskowski

Diffusion models generate high-quality synthetic data. They operate by defining a continuous-time forward process which gradually adds Gaussian noise to data until fully corrupted. The corresponding reverse process progressively "denoises"…

Goldreich suggested candidates of one-way functions and pseudorandom generators included in $\mathsf{NC}^0$. It is known that randomly generated Goldreich's generator using $(r-1)$-wise independent predicates with $n$ input variables and…

Cryptography and Security · Computer Science 2014-06-03 Ryuhei Mori , Takeshi Koshiba , Osamu Watanabe , Masaki Yamamoto

We consider discrete, iterative load balancing via matchings on arbitrary graphs. Initially each node holds a certain number of tokens, defining the load of the node, and the objective is to redistribute the tokens such that eventually each…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-20 Petra Berenbrink , Robert Elsässer , Tom Friedetzky , Hamed Hosseinpour , Dominik Kaaser , Peter Kling , Thomas Sauerwald

We study the fundamental task of estimating the median of an underlying distribution from a finite number of samples, under pure differential privacy constraints. We focus on distributions satisfying the minimal assumption that they have a…

Statistics Theory · Mathematics 2020-11-13 Christos Tzamos , Emmanouil-Vasileios Vlatakis-Gkaragkounis , Ilias Zadik

The logarithmic slope of the diffractive structure function is a potential observable scanning the hard and soft contributions in diffraction, allowing to disentangle the QCD dynamics. We report our calculations concerning this quantity, in…

High Energy Physics - Phenomenology · Physics 2007-05-23 M. B. Gay Ducati , V. P. Gonçalves , M. V. T. Machado