New measures found in 3-uniform geometry.
problem Understanding non-flat uniform measures in geometric measure theory.
method Combining combinatorial methods and distance symmetry properties.
result Infinite family of 3-uniform measures constructed.
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48 results for “uniform measure”
Paper proves the maximum Hausdorff dimension of singular set for n-uniform measures.
problem Classifying uniform measures and understanding their singular sets.
method Using the Kowalski-Preiss cone to construct an n-uniform measure and proving its singular set's Hausdorff dimension.
result The Hausdorff dimension of the singular set of any n-uniform measure is at most n-3.
The paper classifies 1-dimensional uniform measures in various dimensions.
problem Classifying uniformly distributed measures of dimension 1 in general codimension.
method Analyzing measures with connected 1-dimensional support and providing a partial classification for general measures.
result Uniform measures with connected 1-dimensional support are homogeneous measures.
Establishes a link between risk measures and uniform integrability in finance.
problem Understanding uniform integrability in the context of financial risk measures.
method Introduces the folding score of distortion risk measures to study uniform integrability directly with gains and losses.
result Obtains three sets of equivalent conditions for uniform integrability involving coherent risk measures.
Uniform rectifiability proven for sets with Poincaré inequalities.
problem Uniform rectifiability of sets with Poincaré inequalities.
method Weak -Poincaré inequality and surface measure.
result Uniform rectifiability achieved for sets supporting such inequalities.
Uniform convergence of metrics on surfaces with bounded curvature measures proved.
problem Proving uniform convergence of metrics on Alexandrov surfaces with bounded integral curvature.
method Weak convergence of measures and analytic approximation of metrics.
result Uniform convergence of metrics on Alexandrov surfaces proved.
Unique continuation property for measures in high dimensions.
problem Understanding the structure of measures in high-dimensional spaces.
method Analyzing locally uniformly distributed measures and their supports.
result Locally uniformly distributed measures satisfy a unique continuation property.
Metrizable uniform spacesmath.GT
Three themes of general topology: quotient spaces; absolute retracts; and inverse limits - are reapproached here in the setting of metrizable uniform spaces, with an eye to applications in geometric and algebraic topology. The results include: 1) If f: A -> Y is a uniformly continuous map, where X and Y are metric spac…
In this thesis a connection between the worlds of discrete and continuous conformal geometry is explored. Specifically, a disk pattern production theroem is proved using an energy which measures how ``uniform'' the angle data of a triangulation is, see also math.DG/0002150. Then this energy is averaged over all the Del…
Uniform Poincaré inequalities established for various metric spaces.
problem Establishing uniform Poincaré inequalities on different metric spaces.
method Proper geodesic metric spaces equipped with a Borel measure. Local Poincaré inequality and volume conditions are used to derive uniform Poincaré inequalities.
result Uniform Poincaré inequalities are established for various metric spaces including hyperbolic spaces and covers of compact spaces.
Uniform entropy bound for Ricci shrinkers with bounded curvature.
problem Bounding entropy for Ricci shrinkers with specific curvature constraints.
method Establishing uniform entropy bounds for simply connected Ricci shrinkers with a finite second homotopy group and uniform curvature bounds.
result Uniform entropy bound for simply connected Ricci shrinkers with a finite second homotopy group and uniform curvature bounds.
New learning rule for quantum measurement classes overcomes uniform convergence issues.
problem Characterizing learnability of POVM hypothesis classes in quantum settings.
method Introduced a new learning rule called denoised ERM to address uniform convergence issues.
result Characterized learnability conditions and sample complexity bounds for POVM classes.
Paper proves integrability and entropy compactness for Kähler potentials with uniform log-log threshold.
problem Integrability and entropy compactness for Kähler potentials with specific density.
method Skoda-Zeriahi type integrability theorem and log-log threshold detection.
result Positivity of integrability threshold and entropy compactness for uniform log-log threshold.
New material groupoid theory subdivides non-uniform bodies into smoothly uniform parts and isolated points.
problem Lack of differentiability in material bodies leads to non-uniformity.
method Introducing material groupoid and material distribution to study non-uniform bodies rigorously.
result Material bodies can be subdivided into smoothly uniform parts and isolated points.
In this paper, we study the asymptotic behavior of the volume of spheres in metric measure spaces. We first introduce a general setting adapted to the study of asymptotic isoperimetry in a general class of metric measure spaces. We then introduce a notion of "being asymptotically isoperimetric" for a family of finite a…
Paper extends learning theory to dependent data with uniform risk bounds.
problem Learning with dependent data sequences.
method Derives uniform risk bounds for dependent data using VC-dimension and Rademacher complexity.
result Standard classification risk bounds hold for dependent data, same as for independent data.
Unified framework for uniform signal recovery in nonlinear GCS with 1-bit/quantized measurements.
problem Uniform recovery guarantees for nonlinear generative compressed sensing.
method Unified framework using generalized Lasso and Lipschitz approximation.
result Uniform recovery of all signals in the ball up to an error of ε using approximately O(k/ε^2) samples.
Confounder Detection in High Dimensional Linear Models using First Moments of Spectral Measuresstat.ML
Method detects confounders in high-dimensional linear models using spectral measure first moments.
problem Detecting confounders in high-dimensional linear models.
method Uses the first moment of the spectral measure of the regression coefficient vector.
result Statistical asymmetry in first moments of spectral measures indicates the presence of confounders.
Prove a global shadow lemma for Patterson-Sullivan measures associated with relatively Morse subgroups in higher-rank semisimple Lie groups.
problem Prove a global shadow lemma for Patterson-Sullivan measures associated with relatively Morse subgroups in higher-rank semisimple Lie groups.
method Prove a global shadow lemma for Patterson-Sullivan measures associated with relatively Morse subgroups in higher-rank semisimple Lie groups.
result Prove a global shadow lemma for Patterson-Sullivan measures associated with relatively Morse subgroups in higher-rank semisimple Lie groups.
NUTS mixing time scales as d^(1/4) for Gaussian distributions.
problem Improving the efficiency of the No-U-Turn Sampler (NUTS) for Gaussian distributions.
method Coupling argument leveraging geometric structure of Gaussian concentration, uniformity analysis of NUTS transitions.
result The mixing time of NUTS scales as d^(1/4) for Gaussian distributions, up to logarithmic factors.
Implementing -NN classification using Gromov--Wasserstein distances
problem Comparing metric measure spaces
method Gromov--Wasserstein and fused Gromov--Wasserstein distances
result Universal consistency of -NN classifiers
Paper introduces Uniform-PAC framework for RL, bridging PAC and regret.
problem Measuring and guaranteeing performance in reinforcement learning.
method Introduces Uniform-PAC framework, derives high probability regret guarantees.
result Demonstrates new algorithm achieving optimal regret and PAC guarantees.
For any family of measurable sets in a probability space, we show that either (i) the family has infinite Vapnik-Chervonenkis (VC) dimension or (ii) for every epsilon > 0 there is a finite partition pi such the pi-boundary of each set has measure at most epsilon. Immediate corollaries include the fact that a family wit…
New Fourier analysis method for non-uniform Boolean hypercube.
problem Non-uniform probability measures on the Boolean hypercube.
method ANOVA-based decomposition, explicit basis, least squares problem.
result Generalization of Fourier analysis for arbitrary probability measures.
Convergence of Siegel-Veech constants for weakly convergent measures on translation surfaces.
problem Convergence of Siegel-Veech constants for weakly convergent measures on translation surfaces.
method Recurrence result related to Eskin-Masur techniques, measure equidistribution result.
result Convergence of sequences of Siegel-Veech constants associated to Teichmüller curves in genus two.
Entropy for uniform hypergraphs defined via tensor theory.
problem Entropy calculation for uniform hypergraphs.
method Probability distribution of generalized singular values from Laplacian tensors, Shannon entropy formula.
result Tensor entropy is a measure of regularity for uniform hypergraphs.
The paper studies properties of Sliced Wasserstein energy for discrete measures.
problem Optimizing discrete probability measures using Sliced Wasserstein loss.
method Investigates the regularity and optimisation properties of the Sliced Wasserstein energy and its Monte-Carlo approximation.
result Convergence results on the critical points of Monte-Carlo approximations to the Sliced Wasserstein energy.
ANNs overcome curse of dimensionality for heat equation uniform errors.
problem Approximating high-dimensional heat equations with neural networks.
method Developed techniques to estimate uniform -error.
result ANNs' parameters grow polynomially with dimension and precision.
Study shows uniform-time chaos propagation in mean field Langevin dynamics.
problem Understanding the convergence of marginal distributions in mean field dynamics.
method Assumed functional convexity of energy, used -convergence and Wasserstein metrics.
result Uniform-in-time propagation of chaos proved in both -Wasserstein and relative entropy.
Uniformizes compact complex manifolds via Anosov representations.
problem Uniformization of compact complex manifolds.
method Anosov homomorphisms with small limit sets.
result Local homeomorphism of character variety to Teichmüller space.
Uniform systole bounds for arithmetic orbifolds and number fields.
problem Bounding systole lengths in arithmetic orbifolds.
method Geometric methods and Mahler measure.
result Uniform lower bounds for systole lengths.
Conformal Test Martingales can be 'blind' to significant changes in data distribution.
problem The converse of exchangeability does not hold, leading to potential blindness of CTMs.
method Explicit construction of -cryptic change-point using bivariate Gaussian distributions.
result CTMs can be perfectly cryptic to a significant change in marginal means.
Study uniform learnability of binary classification networks with communication.
problem Learning a network with communication between vertices from uniform ergodic Random Graph Process.
method Introduced structural Rademacher complexity and used martingale method and Marton's coupling.
result Uniform learnability as worst-case theoretical limits for binary classification problems.
The study characterizes train tracks and measured laminations on infinite surfaces.
problem Characterizing geodesic laminations on infinite surfaces.
method Defining train tracks and parametrizing measured laminations by edge weight systems.
result A homeomorphism exists between bounded measured laminations and edge weight systems.
New stability results for sequences of metric measure spaces with uniform Ricci bounds from belowmath.MG
Paper provides stability results for metric measure spaces with uniform Ricci bounds.
problem Stability of metric measure spaces with Ricci bounds.
method Extrinsic embedding and Mosco convergence of Cheeger's energies.
result Continuity of Cheeger's constant and stability of Ricci bounds.
Uniform heat kernel bounds lead to synthetic Ricci curvature conditions for Lipschitz manifolds.
problem Establishing synthetic Ricci curvature conditions for Lipschitz manifolds.
method Uniform heat kernel bounds and synthetic Ricci curvature conditions.
result Uniform heat kernel bounds lead to synthetic Ricci curvature conditions for Lipschitz manifolds.
MAS scores cluster size consistency from points, robust to label changes.
problem Desired uniformity in cluster sizes, stability under label perturbations.
method Mass Agreement Score (MAS) measures point-centric cluster size consistency, robust to label changes.
result MAS yields similar scores for partitions with similar bulk structure, sensitive to genuine redistribution of cluster mass.
Paper derives uniform error bounds for Gaussian process regression for safer control applications.
problem Quantifying model error in Gaussian process regression for safety-critical applications.
method Employing Gaussian process distribution and continuity arguments, derive uniform error bounds under weaker assumptions.
result Derives novel uniform error bounds for Gaussian process regression under weaker assumptions.
The study examines metrics on Riemannian spaces with bounded properties and finds conditions for Lipschitz and uniform bounds.
problem Investigating bounded rough Riemannian metrics and their properties.
method Analyzing the structure of bounded rough Riemannian metrics and finding conditions for Lipschitz and uniform bounds.
result Weak conditions are identified for Lipschitz and uniform bounds on the metrics.
Uniform Closure Method and Bayes classifier perform similarly in classifying open knots.
problem Classifying knots in open macromolecular chains.
method Used the Bayes MAP classifier and compared it to the Uniform Closure Method.
result Both methods have comparable accuracy and positive predictive value.
Unified framework for robust clustering under various dissimilarity measures.
problem Improving center-based clustering methods to handle outliers and non-Euclidean data.
method Median-of-Means (MoM) estimation framework with uniform concentration bounds.
result Strong consistency and error rate of under mild conditions.
The paper develops a robust signal estimation method for noisy measurements from generative models.
problem Signal estimation from noisy non-linear measurements with adversarial corruptions.
method Generalized Lasso approach with sub-Gaussian measurements and adversarial noise consideration.
result The method requires $O\left(\frac{k}{ε^2}\log L
ight)$ samples for -error recovery, robust to adversarial noise.
The paper explores stability and coercivity for toric polarizations, linking them to K-energy.
problem Stability and coercivity of K-energy for toric polarizations.
method Introduces uniform K-stability and its relationship with coercivity, considering group actions and reduced norms.
result Uniform stability is equivalent to coercivity of the K-energy in the toric case.
Improved error estimate for SGLD sampling algorithm.
problem Establishing a precise error bound for SGLD.
method Sharp uniform-in-time error estimate for SGLD under mild assumptions.
result Uniform-in-time bound for KL-divergence between SGLD and Langevin diffusion.
Paper provides uniform deviation bounds for unbounded loss functions, improving k-Means clustering bounds.
problem Uniform deviation bounds for unbounded loss functions, specifically k-Means clustering.
method Novel framework to obtain uniform deviation bounds for unbounded loss functions.
result Improved bounds for k-Means clustering under weak assumptions, achieving $\mathcal{O}\left(m^{-\frac12}
ight)$ rate.
Uniform drift estimates found for random walks on graph products.
problem Finding uniform lower bounds on drift for random walks on graph products.
method Extending Gouëzel's argument and introducing the combinatorial notion of piling.
result Uniform lower bounds on the drift for a family of random walks on graph products.
Uniform heat kernel and diffusion bridge asymptotics for sub-Riemannian geometry.
problem Analyzing sub-Riemannian heat kernels and their derivatives on incomplete manifolds.
method Localized asymptotic analysis, focusing on minimizing geodesics and the non-abnormal cut locus.
result Uniform bounds and expansions for heat kernels and their derivatives on compacts, including the diffusion bridge measure.
Predict social trust using 1-bit measurements and non-uniform sampling.
problem Predict social trust in social networks with sign measurements and non-uniform sampling.
method Propose a 1-bit max-norm constrained formulation and use a projected gradient decent algorithm.
result Demonstrated superior performance on benchmark datasets.