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arXiv research

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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140280420560 · Jun 202019922001200920172026
48 results for class means

The paper examines translating solitons and their relation to Lagrangian mean curvature flows with zero Maslov class.

problem Understanding the behavior of Lagrangian translating solitons near Type II singularities.
method Analyzes necessary conditions for blow-up limits and applies to open questions.
result Provides a necessary condition for blow-up limits of Lagrangian mean curvature flows with zero Maslov class.

The paper proves rigidity theorems for Type II singularities in Lagrangian flows.

problem Understanding Type II singularities in Lagrangian flows with zero Maslov class.
method Rigidity theorems for blow-up limits of Type II singularities.
result Generalized previous results from 2D to arbitrary dimensions.

This note finds closed-form solutions for mean-risk portfolios using a specific type of mixture distribution.

problem Finding optimal portfolios under mean-risk criteria for general distributions.
method Using normal mean-variance mixture (NMVM) distributions, the paper derives closed-form expressions for mean-risk frontiers by optimizing a Markowitz model with adjusted return vectors.
result Closed-form solutions for mean-risk portfolios are found for return vectors following NMVM distributions.

This paper extends neural collapse to class-imbalanced datasets using an unconstrained ReLU feature model.

problem Understanding neural collapse in class-imbalanced datasets with cross-entropy loss.
method Generalized neural collapse to class-imbalanced settings using an unconstrained ReLU feature model.
result Class-means converge to orthogonal vectors with different lengths, and classifier weights align to these vectors.

In recent years, more machine learning algorithms have been applied to odor classification. These odor classification algorithms usually assume that the training datasets are static. However, for some odor recognition tasks, new odor classes continually emerge. That is, the odor datasets are dynamically growing while b…

2018-01-08abs ↗pdf ↗

Study finds polynomial convergence rate for Farey sequences linked to Riemann hypothesis.

problem Understanding convergence rates of maximum mean discrepancies for Farey sequences.
method Identifying positive-semidefinite kernels and their polynomial convergence rates.
result Polynomial convergence rate of maximum mean discrepancies of Farey sequences is equivalent to the Riemann hypothesis.

Constructs foliations of lightcones using surfaces of constant spacetime mean curvature.

problem Creating foliations of lightcones with specific geometric properties.
method Employing a geometric flow inspired by Huisken-Yau's approach for Riemannian settings.
result Initial data converges exponentially to an STCMC surface under area preserving null mean curvature flow.

A mean function in reproducing kernel Hilbert space, or a kernel mean, is an important part of many applications ranging from kernel principal component analysis to Hilbert-space embedding of distributions. Given finite samples, an empirical average is the standard estimate for the true kernel mean. We show that this e…

2013-06-04abs ↗pdf ↗

Study shows different behaviors of noncompact hypersurfaces under mean curvature flow.

problem Analyzing stability of noncompact hypersurfaces with curvature blowup.
method Numerical overlap method to construct global solutions.
result Existence of near and far classes of initial data leading to distinct behaviors.

E2^2CM uses class means for efficient early exits in neural networks.

problem Efficient early exits in neural networks with low computational cost.
method Early Exit Class Means (E2^2CM) based on class means of samples, without gradient-based training.
result E2^2CM achieves higher accuracy with fixed training time budget and boosts existing early exit schemes.

We show that any strictly mean convex translator of dimension n3n\geq 3 which admits a cylindrical estimate and a corresponding gradient estimate is rotationally symmetric. As a consequence, we deduce that any translating solution of the mean curvature flow which arises as a blow-up limit of a two-convex mean curvature…

2016-05-31abs ↗pdf ↗

Generalizing the construction of the Maslov class for a Lagrangian embedding in a symplectic vector space, we prove that it is possible to give a consistent definition of this class for any Lagrangian submanifold of a Calabi-Yau manifold. Moreover, we prove that this class can be represented by the contraction of the K…

2000-01-12abs ↗pdf ↗

Deep nets exhibit 'Neural Collapse' during training's final phase, simplifying decision-making.

problem Understanding and optimizing deep learning training phases.
method Direct measurements on three deepnet architectures across seven datasets.
result Deep nets exhibit 'Neural Collapse' during training's final phase, simplifying decision-making.

In this note we study a large class of mean curvature type flows of graphs in product manifold N×RN\times R where N is a closed Riemann- ian manifold. Their speeds are the mean curvature of graphs plus a prescribed function. We establish long time existence and uniformly convergence of those flows with a barrier conditi…

2017-12-19abs ↗pdf ↗

The paper bounds the L2L^2-norm of Euler class for foliations on 3-manifolds.

problem Bounding the L2L^2-norm of the Euler class for foliations on 3-manifolds.
method Using constants bounding volume, radius of injectivity, sectional curvature, and mean curvature of leaves.
result Only finitely many cohomological classes can be realized by the Euler class of a transversely oriented foliation with bounded mean curvature.

Paper establishes sufficient condition for comparing linear combinations of infinite-mean risks.

problem Comparing linear combinations of infinite-mean risks under stochastic dominance.
method Introduced a new class of distributions and used majorization order to compare weights.
result Linear combinations of random variables are stochastically larger when their weight vectors are smaller in majorization order.

Unified framework for shrinkage, thresholding, and regularization in normal mean estimation and linear regression.

problem Estimation of normal mean in multivariate settings with correlated observations.
method Approximate risk minimization over a functional class of shrinkage-thresholding rules.
result Unified estimator NOMAD for shrinkage, thresholding, and regularization.

This study solves a Dirichlet problem for specific elliptic equations on Riemannian manifolds with concave boundaries.

problem Solving the Dirichlet problem for degenerate elliptic equations on Riemannian manifolds with mean concave boundaries.
method The proof relies on a quantitative boundary estimate.
result Analogous results are obtained in complex variables and on certain product manifolds.

A special formula for the total mean curvature of an ovaloid is derived. This formula allows us to extend the notion of the mean curvature to the class of boundaries of strictly convex sets. Moreover, some integral formula for ovaloids is proved.

2019-12-23abs ↗pdf ↗

In this article, we will use the harmonic mean curvature flow to prove a new class of Alexandrov-Fenchel type inequalities for strictly convex hypersurfaces in hyperbolic space in terms of total curvature, which is the integral of Gaussian curvature on the hypersurface. We will also use the harmonic mean curvature flow…

2019-03-14abs ↗pdf ↗

Study minimizes Willmore energy with constraints on surface properties.

problem Minimizing Willmore energy under specific surface properties.
method Adapting Keller-Mondino-Rivière, Bauer-Kuwert, and Ndiaye-Schätzle methods.
result Existence of smooth minimizers for a broad range of constraints.

Study timelike meridian surfaces in Minkowski 4-space with specific properties.

problem Characterize timelike meridian surfaces with special properties in Minkowski 4-space.
method Analyze different classes of timelike meridian surfaces with constant Gauss curvature, mean curvature, and parallel normalized mean curvature vector field.
result Explicit solutions to PDEs describing timelike surfaces with parallel normalized mean curvature vector field.

Paper extends stochastic dominance for compound binomial distributions.

problem Stochastic dominance for infinite-mean random variables.
method Investigates properties and inclusion relationships of distribution classes, extends results to compound binomial distributions.
result Establishes necessary and sufficient conditions for first-order stochastic dominance preservation.

Optimally regularizes boundaries in the Heisenberg group with prescribed curvature.

problem Optimizing boundaries with prescribed sub-Finsler mean curvature in the Heisenberg group.
method Analyzes critical sets of the prescribed mean curvature functional in the Heisenberg group.
result Characteristic curves of critical sets are C2C^2-regular, optimal in the Heisenberg group.

Learning from class-imbalanced data continues to be a common and challenging problem in supervised learning as standard classification algorithms are designed to handle balanced class distributions. While different strategies exist to tackle this problem, methods which generate artificial data to achieve a balanced cla…

2017-11-02abs ↗pdf ↗

We prove that the mean Euler characteristic of a Gorenstein toric contact manifold, i.e. a good toric contact manifold with zero first Chern class, is equal to half the normalized volume of the corresponding toric diagram and give some applications. A particularly interesting one, obtained using a result of Batyrev and…

2016-11-02abs ↗pdf ↗