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Given a bounded class of functions G and independent random variables X1, . . . , Xn, we provide an upper bound for the expectation of the supremum of the empirical process over elements of G having a small variance. Our bound applies in…

Probability · Mathematics 2015-09-08 Yannick Baraud

We analyze a random greedy process to construct $q$-uniform linear hypergraphs using the differential equation method. We show for $q=o(\sqrt{\log n})$, that this process yields a hypergraph with $\frac{n(n-1)}{q(q-1)}(1-o(1))$ edges. We…

Combinatorics · Mathematics 2024-12-18 Sayok Chakravarty , Nicholas Spanier

Generalized entropies and relative entropies are the subject of active research. Similar to the standard relative entropy, the relative $q$-entropy is generally unbounded for $q>1$. Upper bounds on the quantum relative $q$-entropy in terms…

Mathematical Physics · Physics 2011-06-28 Alexey E. Rastegin

Lower and upper bounds on the size of a covering of subspaces in the Grassmann graph $\cG_q(n,r)$ by subspaces from the Grassmann graph $\cG_q(n,k)$, $k \geq r$, are discussed. The problem is of interest from four points of view: coding…

Combinatorics · Mathematics 2012-10-12 Tuvi Etzion

We develop a nonparametric extension of the sequential generalized likelihood ratio (GLR) test and corresponding time-uniform confidence sequences for the mean of a univariate distribution. By utilizing a geometric interpretation of the GLR…

Statistics Theory · Mathematics 2021-05-17 Jaehyeok Shin , Aaditya Ramdas , Alessandro Rinaldo

We obtain the tail probability of generalized sub-Gaussian canonical processes. It can be viewed as a variant of the Bernstein-type inequality in the i.i.d case, and we further get a tighter bound of concentration inequality through…

Probability · Mathematics 2024-02-02 Yiming Chen , Yuxuan Wang , Kefan Zhu

Let $G$ be either the Grigorchuk $2$-group or one of the Gupta-Sidki $p$-groups. We give new upper bounds for the diameters of the quotients of $G$ by its level stabilisers, as well as other natural sequences of finite-index normal…

Group Theory · Mathematics 2017-03-20 Henry Bradford

Gaussian processes have become a promising tool for various safety-critical settings, since the posterior variance can be used to directly estimate the model error and quantify risk. However, state-of-the-art techniques for safety-critical…

Machine Learning · Computer Science 2022-07-22 Alexandre Capone , Armin Lederer , Sandra Hirche

We obtain Gaussian upper bounds for heat kernels of higher order differential operators with Dirichlet boundary conditions on bounded domains in $\R^N$. The bounds exhibit explicitly the nature of the spatial decay of the heat kernel close…

Analysis of PDEs · Mathematics 2012-08-01 Narinder Claire

Introducing inequality constraints in Gaussian process (GP) models can lead to more realistic uncertainties in learning a great variety of real-world problems. We consider the finite-dimensional Gaussian approach from Maatouk and Bay (2017)…

Machine Learning · Statistics 2021-11-04 Andrés F. López-Lopera , François Bachoc , Nicolas Durrande , Olivier Roustant

We derive moment and tail estimates for Gaussian chaoses of arbitrary order with values in Banach spaces. We formulate a conjecture regarding two-sided estimates and show that it holds in a certain class of Banach spaces including L_q…

Probability · Mathematics 2021-06-08 Radosław Adamczak , Rafał Latała , Rafał Meller

Let $G$ be a finite simple graph and $I(G)$ denote the corresponding edge ideal. In this paper, we obtain upper bounds for the Castelnuovo-Mumford regularity of $I(G)^q$ in terms of certain combinatorial invariants associated with $G$. We…

Commutative Algebra · Mathematics 2021-02-02 A. V. Jayanthan , S. Selvaraja

Let $\mathcal{G}(\frak{g}_1,\frak{g}_2)$ be the class of all probability distribution functions of positive random variables having the given first two moments $\frak{g}_1$ and $\frak{g}_2$. Let $G_1(x)$ and $G_2(x)$ be two probability…

Probability · Mathematics 2009-11-20 Vyacheslav M. Abramov

New lower and upper bounds on the reliability function of typewriter channels are given. Our lower bounds improve upon the (multiletter) expurgated bound of Gallager, furnishing a new and simple counterexample to a conjecture made in 1967…

Information Theory · Computer Science 2017-11-02 M. Dalai , Y. Polyanskiy

We provide numerical indications of the $q$-generalised central limit theorem that has been conjectured (Tsallis 2004) in nonextensive statistical mechanics. We focus on $N$ binary random variables correlated in a {\it scale-invariant} way.…

Statistical Mechanics · Physics 2007-05-23 Luis G. Moyano , Constantino Tsallis , Murray Gell-Mann

Let $(u_n)_{n \geq 0}$ be a non-degenerate Lucas sequence, given by the relation $u_n=a_1 u_{n-1}+a_2 u_{n-2}$. Let $\ell_u(m)=lcm(m, z_u(m))$, for $(m,a_2)=1$, where $z_u(m)$ is the rank of appearance of $m$ in $u_n$. We prove that…

Number Theory · Mathematics 2019-01-08 Daniele Mastrostefano

Let $f$ be a $SL(2,\mathbb{Z})$ holomorphic cusp form or the Eisenstien series $E(z,1/2)$ and $\pi$ be a $SL(3,\mathbb{Z})$ Hecke-Maass cusp form with its Langlands parameter $\mu$ in generic position i.e. away from Weyl chamber walls and…

Number Theory · Mathematics 2022-06-23 Prahlad Sharma

Let $S$ be a minimal irregular surface of general type, whose Albanese map induces a hyperelliptic fibration $f:\,S \to B$ of genus $g$.We prove a quadratic upper bound on the genus $g$, i.e., $g\leq h\big(\chi(\mathcal{O}_S)\big)$, where…

Algebraic Geometry · Mathematics 2025-05-07 Songbo Ling , Xin Lü

This paper concerns parameterized convex infinite (or semi-infinite) inequality systems whose decision variables run over general infinite-dimensional Banach (resp. finite-dimensional) spaces and that are indexed by an arbitrary fixed set T…

Optimization and Control · Mathematics 2011-02-07 M. J. CÁnovas , M. A. LÓpez , B. S. Mordukhovich , J. Parra

Generalization error bounds are essential for comprehending how well machine learning models work. In this work, we suggest a novel method, i.e., the Auxiliary Distribution Method, that leads to new upper bounds on expected generalization…

Machine Learning · Computer Science 2024-04-18 Gholamali Aminian , Saeed Masiha , Laura Toni , Miguel R. D. Rodrigues