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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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295886115 · May 202619922001200920172026
48 results for Moment inequalities

A classical result of Aubin states that the constant in Moser-Trudinger-Onofri inequality on S2\mathbb{S}^{2} 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…

2019-09-01abs ↗pdf ↗

New inequality criterion for a mean field equation on spheres.

problem Finding uniqueness in a mean field equation on spheres.
method Established a new Moser-Trudinger-Onofri inequality with a constraint on moments deviation.
result A threshold for deviation is a uniqueness criterion for the mean field equation.

This paper examines how data affects risk measures in uncertain distributions.

problem How does distributional ambiguity affect risk measures?
method Formulated and derived simpler dual problems for infinite and finite dimensional robust moment problems.
result Developed theory and conducted experiments in inventory control and portfolio management.

On compact surfaces, a Green-Wasserstein inequality cannot be improved without the sqrt(log n) factor.

problem Can the Green-Wasserstein inequality be improved without the sqrt(log n) factor?
method Contradiction proof using second-moment estimates and semi-discrete random matching asymptotics.
result It is impossible to remove the sqrt(log n) factor in the inequality on any compact connected surface.

Deviation inequalities for stochastic approximation methods.

problem Establishing bounds on the deviation of stochastic approximation methods.
method Martingale approximation method for separately Lipschitz functions.
result Established various deviation inequalities for stochastic approximation by averaging and minimization.

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…

2017-07-20abs ↗pdf ↗

The paper analyzes extreme risk measures with limited distributional information.

problem Investigating risk measures under partial knowledge of distribution moments and shape.
method Employing probability inequalities and modified Schwarz inequality to derive bounds on distortion risk measures.
result Unified framework for calculating best- and worst-case scenarios of distortion risk measures.

We improve bounds for stochastic processes, especially those with heavy tails.

problem Bounding the concentration of sub-ψψ processes with heavy tails.
method Variational approach to concentration, focusing on sub-Gaussian and other tail conditions.
result First dimension-free self-normalized empirical Bernstein inequality.

New stability framework relaxes boundedness assumptions for generalization bounds.

problem Overly restrictive assumptions for modern learning settings with heavy-tailed or unbounded losses.
method Develops a stability-based framework requiring only finite LpL_p moment conditions.
result Sharp generalization bounds derived for various learning paradigms.

Improved concentration inequalities for sub-Weibull variables enhance statistical and machine learning applications.

problem Improving concentration inequalities for sub-Weibull random variables.
method Developed new concentration inequalities for sums of independent sub-Weibull random variables, including a new sub-Weibull parameter.
result New concentration inequalities with sharper constants and a mixture of sub-Gaussian and sub-Weibull tails.

The article proves Talenti's comparison theorem for Poisson equations on Riemannian manifolds with nonnegative Ricci curvature.

problem Proving Talenti's comparison theorem for Poisson equations on Riemannian manifolds with nonnegative Ricci curvature.
method Analyzing complete noncompact Riemannian manifolds with nonnegative Ricci curvature, applying Talenti's comparison theorem to Poisson equations.
result Obtained the Faber-Krahn inequality for the first eigenvalue of Dirichlet Laplacian, L1L^1- and LL^\infty-moment spectrum, and a reverse Hölder inequality for eigenfunctions of Dirichlet Laplacian.

The paper provides concentration inequalities for Markov chain variance estimators.

problem Estimating the variance of Markov chains with concentration properties.
method Martingale decomposition method for uniformly geometrically ergodic Markov chains.
result Explicit control of the p-th moment of the OBM estimator difference and dependence on p and mixing time.

The paper extends confidence sequences for infinite variance data.

problem Addressing confidence sequences for distributions with infinite variance.
method Establishing lower bounds and deriving tight confidence sequences for relaxed bounded pthp^{th}-moment distributions.
result Derived confidence sequences are tighter than those using Dubins-Savage inequality.

Consider an action of a connected compact Lie group on a compact complex manifold MM, and two equivariant vector bundles LL and EE on MM, with LL 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 …

2015-06-15abs ↗pdf ↗

The paper provides bounds for high-dimensional U-statistics with novel order-explicit inequalities.

problem Bounding the deviation of high-dimensional U-statistics from their Hájek projections.
method Develops novel order-explicit moment inequalities for higher-order Hoeffding components.
result The maximum deviation of a high-dimensional U-statistic from its Hájek projection is of order Op(φbn1log2(dn))O_p(φb n^{-1}\log^2(dn)).

Extends probabilistic approach for Kahler-Einstein metrics on Fano manifolds.

problem Constructing Kahler-Einstein metrics on log Fano manifolds with non-discrete automorphism groups.
method Introduces Gibbs polystability and uses moment map constraint to break symmetry.
result Gibbs polystability conjectured to be equivalent to existence of Kahler-Einstein metric.

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…

2019-09-04abs ↗pdf ↗

Gradient descent on Hadamard manifolds converges to boundary points, solving optimization problems.

problem Optimization on Hadamard manifolds with unbounded convex functions.
method Gradient descent, duality theorem, moment-weight inequality.
result Gradient descent 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…

2009-01-31abs ↗pdf ↗

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…

2003-05-31abs ↗pdf ↗

New statistical test for change-point detection using relative entropy.

problem Offline change-point detection using divergence metrics.
method Study of empirical relative entropy distributions, derivation of approximations, introduction of new Berry-Esseen bounds.
result Theoretical and practical validation of relative entropy for change-point detection.

New algorithm for batch list-decodable linear regression with stronger guarantees.

problem Efficiently list-decoding linear regression with a fraction of corrupted batches.
method Uses higher-order moments and Sum-of-Squares (SoS) certification to achieve better guarantees.
result Achieves substantially smaller minimum batch size and final error, with optimal list size.

A new UCB algorithm for heavy-tailed bandits with near-optimal regret.

problem Sequential decision making in uncertain environments with heavy-tailed rewards.
method Data-driven, distribution-free UCB algorithm combining resampled median-of-means and UCB.
result Near-optimal regret bound for heavy-tailed distributions.

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…

2019-04-02abs ↗pdf ↗

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 …

2019-05-14abs ↗pdf ↗