New proof of Sobolev inequality with constraints on sphere.
arXiv research
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Sharp inequalities in unit ball with constraints on moments.
New method tightens sub-Gaussian concentration inequalities.
A classical result of Aubin states that the constant in Moser-Trudinger-Onofri inequality on can be imporved for furnctions with zero first order moments of the area element. We generalize it to higher order moments case. These new inequalities bear similarity to a sequence of Lebedev-Milin type inequa…
New inequality criterion for a mean field equation on spheres.
This paper examines how data affects risk measures in uncertain distributions.
On compact surfaces, a Green-Wasserstein inequality cannot be improved without the sqrt(log n) factor.
Deviation inequalities for stochastic approximation methods.
The sectional curvature of a compact Riemannian manifold M can be seen as a random variable on the Grassmann bundle of 2-planes in TM endowed with the Fubini-Study volume density. In this article we calculate the moments of this random variable by integrating suitable local Riemannian invariants and discuss the distrib…
The paper analyzes extreme risk measures with limited distributional information.
We improve bounds for stochastic processes, especially those with heavy tails.
Using Jeff Holman's comments in Quantitative Finance to illustrate 4 critical errors students should learn to avoid: 1) Mistaking tails (4th moment) for volatility (2nd moment), 2) Missing Jensen's Inequality, 3) Analyzing the hedging wihout the underlying, 4) The necessity of a numeraire in finance.
Improved CR Sobolev inequalities on CR sphere established.
The paper improves CR Sobolev inequalities and classifies minimizers.
New stability framework relaxes boundedness assumptions for generalization bounds.
Study inequalities for singular values of rectangular matrices.
In this communication, we describe some interrelations between generalized -entropies and a generalized version of Fisher information. In information theory, the de Bruijn identity links the Fisher information and the derivative of the entropy. We show that this identity can be extended to generalized versions of en…
Study intrinsic volume forms on complex hypersurfaces.
Improved concentration inequalities for sub-Weibull variables enhance statistical and machine learning applications.
The article proves Talenti's comparison theorem for Poisson equations on Riemannian manifolds with nonnegative Ricci curvature.
The paper provides concentration inequalities for Markov chain variance estimators.
The paper extends confidence sequences for infinite variance data.
Sharp Gaussian isoperimetry proven along Ricci flow.
Consider an action of a connected compact Lie group on a compact complex manifold , and two equivariant vector bundles and on , with of rank 1. The purpose of this paper is to establish holomorphic Morse inequalities à la Demailly for the invariant part of the Dolbeault cohomology of tensor powers of …
The paper provides bounds for high-dimensional U-statistics with novel order-explicit inequalities.
We prove two weighted geometric inequalities that hold for strictly mean convex and star-shaped hypersurfaces in Euclidean space. The first one involves the weighted area and the area of the hypersurface and also the volume of the region enclosed by the hypersurface. The second one involves the total weighted mean curv…
The paper introduces a new method for tail bounds of random vectors and matrices.
Extends probabilistic approach for Kahler-Einstein metrics on Fano manifolds.
Paper develops robust methods for large-scale testing without tuning parameters.
New PAC-Bayes bounds derived using Legendre transform and f-divergences.
We prove semi-empirical concentration inequalities for random variables which are given as possibly nonlinear functions of independent random variables. These inequalities describe concentration of random variable in terms of the data/distribution-dependent Efron-Stein (ES) estimate of its variance and they do not requ…
We study concentration phenomena of eigenfunctions of the Laplacian on closed Riemannian manifolds. We prove that the volume measure of a closed manifold concentrates around nodal sets of eigenfunctions exponentially. Applying the method of Colding and Minicozzi we also prove restricted exponential concentration inequa…
Gradient descent on Hadamard manifolds converges to boundary points, solving optimization problems.
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of k-generalized statistics, is derived that is particularly suitable to describe the whole spectrum of incomes, from the low-middle income region up…
Donaldson defined a parabolic flow on Kahler manifolds which arises from considering the action of a group of symplectomorphisms on the space of smooth maps between manifolds. One can define a moment map for this action, and then consider the gradient flow of the square of its norm. Chen discovered the same flow from a…
We propose a modified -divergence, give some of its properties, and show that this leads to the definition of a generalized Fisher information. We give generalized Cramér-Rao inequalities, involving this Fisher information, an extension of the Fisher information matrix, and arbitrary norms and power of the estimat…
We revisit the proof by Qin et al. (2014) of bounded regret of the CUCB contextual combinatorial bandit. We demonstrate an error in the proof of volumetric expansion of the moment matrix, used in upper bounding a function of context vector norms. We prove a relaxed inequality that yields the originally-stated regre…
New statistical test for change-point detection using relative entropy.
New algorithm for batch list-decodable linear regression with stronger guarantees.
We adapt to an infinite dimensional ambient space E.R. Reifenberg's epiperimetric inequality and a quantitative version of D. Preiss' second moments computations to establish that the set of regular points of an almost mass minimizing rectifiable chain in is dense in its support, whenever the group of …
A new UCB algorithm for heavy-tailed bandits with near-optimal regret.
We prove trace identities for commutators of operators, which are used to derive sum rules and sharp universal bounds for the eigenvalues of periodic Schroedinger operators and Schroedinger operators on immersed manifolds. In particular, we prove bounds on the eigenvalue lambda_{N+1} in terms of the lower spectrum, bou…
In this work, we study the problem of aggregating a finite number of predictors for nonstationary sub-linear processes. We provide oracle inequalities relying essentially on three ingredients: (1) a uniform bound of the norm of the time varying sub-linear coefficients, (2) a Lipschitz assumption on the predict…
We prove a generalization of the fundamental inequality of Guivarc'h relating entropy, drift and critical exponent to Gibbs measures on geometrically finite quotients of CAT(-1) metric spaces. For random walks with finite superexponential moment, we show that the equality is achieved if and only if the Gibbs density is…
This paper proposes the k-generalized distribution as a model for describing the distribution and dispersion of income within a population. Formulas for the shape, moments and standard tools for inequality measurement - such as the Lorenz curve and the Gini coefficient - are given. A method for parameter estimation is …
We introduce the coupled Ricci-Calabi functional and the coupled H-functional which measure how far from a coupled Kähler-Einstein metric in the sense of Hultgren-Witt Nyström. We first give corresponding moment weight type inequalities which estimate each functional in terms of algebraic invariants. Secondly, we give …
Motivated by the sampling problems and heterogeneity issues common in high- dimensional big datasets, we consider a class of discordant additive index models. We propose method of moments based procedures for estimating the indices of such discordant additive index models in both low and high-dimensional settings. Our …
The paper proves optimizability implies inequalities for sampling.