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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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61121182242 · Jun 202019922001200920172026
48 results for weakly regular

A triangulation of a connected closed surface is called weakly regular if the action of its automorphism group on its vertices is transitive. A triangulation of a connected closed surface is called degree-regular if each of its vertices have the same degree. Clearly, a weakly regular triangulation is degree-regular. In…

2004-03-25abs ↗pdf ↗

A connected combinatorial 2-manifold is called degree-regular if each of its vertices have the same degree. A connected combinatorial 2-manifold is called weakly regular if it has a vertex-transitive automorphism group. Clearly, a weakly regular combinatorial 2-manifold is degree-regular and a degree-regular combinator…

2005-08-05abs ↗pdf ↗

The study shows how to regularize weakly harmonic maps using Sobolev norms and Coulomb frames.

problem Regularity of weakly harmonic maps between Riemannian manifolds.
method New structure equations and Coulomb-frame methods combined with Hardy-BMO duality.
result Sufficient conditions on Sobolev norms ensure full regularity of weakly harmonic maps.

In this paper we consider the existence and regularity of weakly polyharmonic almost complex structures on a compact almost Hermitian manifold M2mM^{2m}. Such objects satisfy the elliptic system weakly [J,ΔmJ]=0[J, Δ^m J]=0. We prove a very general regularity theorem for semilinear systems in critical dimensions (with \emph{cr…

2019-09-22abs ↗pdf ↗

Solves weakly supervised regression using low-rank approximations and manifold regularization.

problem Weakly supervised regression with known, unknown, and uncertain labels.
method Combines manifold regularization and low-rank matrix decomposition for optimization.
result Improves solution quality and stability for large datasets.

In this work we propose to fit a sparse logistic regression model by a weakly convex regularized nonconvex optimization problem. The idea is based on the finding that a weakly convex function as an approximation of the 0\ell_0 pseudo norm is able to better induce sparsity than the commonly used 1\ell_1 norm. For a cl…

2017-08-07abs ↗pdf ↗

We establish the regularity theory for certain critical elliptic systems with an anti-symmetric structure under inhomogeneous Neumann and Dirichlet boundary constraints. As applications, we prove full regularity and smooth estimates at the free boundary for weakly Dirac-harmonic maps from spin Riemann surfaces. Our met…

2013-06-18abs ↗pdf ↗

Unified definition of mass aspect function for weakly regular hyperbolic manifolds.

problem Ambiguity in mass definition for asymptotically hyperbolic manifolds.
method Introduced an ADM-style mass aspect function for broad asymptotics and low regularity.
result Unified mass aspect function exhibits favorable covariance properties.

Paper establishes NE existence and efficient algorithms for weakly monotone GMFGs.

problem Existence and efficient learning of Nash Equilibrium in λλ-regularized GMFGs.
method Establishes existence of NE for any λλ-regularized GMFGs. Proposes efficient algorithms for weakly monotone GMFGs.
result Efficient algorithms for weakly monotone GMFGs with provable convergence.

Paper establishes maximum principles for weakly 1-coercive operators.

problem Finding conditions for solutions of differential equations to satisfy specific inequalities.
method Maximum principles for weakly 1-coercive operators on Riemannian manifolds.
result Guarantees that solutions of certain differential equations satisfy specific inequalities.

Unified approach tackles high-dimensional tensor bandits with convex optimization and weakly decomposable regularizers.

problem Challenges in high-dimensional generalized tensor bandits where existing algorithms fail.
method Proposes a generalized linear tensor bandits algorithm with a unified analytical framework using convex optimization and weakly decomposable regularizers.
result Unified analytical framework provides better bounds and broader applicability compared to existing methods.

Paper develops proper, lower-bounded losses for weakly supervised classification.

problem Weakly supervised classification with corrupted labels.
method Representation theorem for proper losses, derived condition for lower-boundedness, generalized logit squeezing.
result Proper and lower-bounded losses for weak-label learning.

We review recent work on the Einstein equations of general relativity when the curvature is defined in a weak sense. Weakly regular spacetimes are constructed, in which impulsive gravitational waves, as well as shock waves, propagate.

2010-09-09abs ↗pdf ↗

For any nn-dimensional compact spin Riemannian manifold MM with a given spin structure and a spinor bundle ΣMΣM, and any compact Riemannian manifold NN, we show an εε-regularity theorem for weakly Dirac-harmonic maps . As a consequence, any weakly Dirac-harmonic map is proven to be smooth when n = 2. A weak converg…

2008-10-10abs ↗pdf ↗

Study on weakly G-slim complexes and non-positive immersions for group presentations.

problem Conditions for non-positive immersions in group presentations.
method Investigation of weakly G-slim complexes and their relationship to left-orderable groups.
result Conditions on generalized Wirtinger presentations guaranteeing non-positive immersions for their associated 2-complexes.

In this paper, we investigate the ergodic and rigidity properties of weakly hyperbolic group actions. Motivated by classical theorems describing Anosov diffeomorphisms, we obtain two main results: First, all C^2 volume preserving weakly hyperbolic actions on closed manifolds are ergodic. This result generalizes Anosov'…

2005-11-11abs ↗pdf ↗

New convergence rates found for PnP methods using MMSE denoisers.

problem Asymptotic convergence of PnP methods with MMSE denoisers.
method Explicitly represented MMSE denoiser as an upper Moreau envelope, derived sublinear convergence rates.
result First sublinear convergence guarantee for PnP proximal gradient descent with MMSE denoiser.

The study proves a theorem on Riemannian manifolds for wedge products of weakly convergent differential forms.

problem Analyzing the limiting behavior of wedge products of weakly convergent differential forms on Riemannian manifolds.
method Formulating and proving compensated compactness theorems for wedge products of differential forms on closed Riemannian manifolds.
result The theorem generalizes the div-curl lemma for vectorfields and applies to critical regularity exponents.

Method estimates noise transition matrix from noisy labels without relying on unreliable class-posterior estimation.

problem Estimating noise transition matrix from noisy data.
method Total variation regularization to encourage distinguishable predicted probabilities.
result Consistent estimator of the noise transition matrix under mild assumptions.

In this paper we prove that every definable set has a definable triangulation which is locally Lipschitz and weakly bi-Lipschitz on the natural simplicial stratification of the simplicial complex. We also distinguish a class T of regularity conditions and give a universal construction of a definable triangulation with …

2009-04-08abs ↗pdf ↗

JoCoR improves deep learning with noisy labels by reducing network diversity.

problem Learning with noisy labels in deep learning.
method JoCoR uses two networks to make predictions, calculates a joint loss with Co-Regularization, and updates both networks simultaneously.
result JoCoR outperforms state-of-the-art approaches in learning with noisy labels.

Convex surfaces derived from specific Riemannian manifolds with high regularity.

problem Proving convexity of surfaces derived from Riemannian manifolds.
method Analyzing solutions to the very weak Monge-Ampère equation.
result Proved convexity of weakly regular surfaces with nonnegative intrinsic curvature.

Let MM be a C2C^2-smooth Riemannian manifold with boundary and NN a complete C2C^2-smooth Riemannian manifold. We show that each stationary pp-harmonic mapping u ⁣:MNu\colon M\to N, whose image lies in a compact subset of NN, is locally C1,αC^{1,α} for some α(0,1)α\in (0,1), provided that NN is simply connected and has non-…

2018-02-03abs ↗pdf ↗

New algorithm solves complex non-convex problems efficiently.

problem Non-smooth non-convex problems with weakly convex and strongly concave components.
method Stochastic Moreau envelope approximate gradient method (SMAG).
result First single-loop algorithm with state-of-the-art convergence rate.

In this paper, we prove estimates and quantitative regularity results for the harmonic map flow. First, we consider H^1_loc-maps u defined on a parabolic ball P\subset M\times R and with target manifold N, that have bounded Dirichlet-energy and Struwe-energy. We define a quantitative stratification, which groups togeth…

2013-08-12abs ↗pdf ↗

We show that closed hypersurfaces in Euclidean space with nonnegative scalar curvature are weakly mean convex. In contrast, the statement is no longer true if the scalar curvature is replaced by the k-th mean curvature, for k greater than 2, as we construct the counter-examples for all k greater than 2. Our proof relie…

2011-02-28abs ↗pdf ↗

In a recent paper the author introduced a new method based on viscosity techniques for producing minimal surfaces by minmax arguments. The present work corresponds to the regularity part of the method. Precisely we establish that any weakly conformal W1,2W^{1,2} map from a riemann surface SS into a closed oriented sub-m…

2016-10-31abs ↗pdf ↗

Quaternionic analysis proves minimum of Willmore functional on Riemann surfaces.

problem Finding minimum of Willmore functional on Riemann surfaces.
method Extending quaternionic analysis to weakly conformal maps and using Darboux transformation.
result Minimum of Willmore functional on Riemann surfaces is achieved by weakly conformal maps.

This paper studies aligning knowledge graphs from different sources or languages. Most existing methods train supervised methods for the alignment, which usually require a large number of aligned knowledge triplets. However, such a large number of aligned knowledge triplets may not be available or are expensive to obta…

2019-07-06abs ↗pdf ↗