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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.

168,657 papers · 148 categories

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105210314419 · Jun 202019922001200920172026
48 results for local regularization

We introduce a notion of non-local almost minimal boundaries similar to that introduced by Almgren in geometric measure theory. Extending methods developed recently for non-local minimal surfaces we prove that flat non-local almost minimal boundaries are smooth. This can be viewed as a non-local version of the Almgren-…

2010-03-12abs ↗pdf ↗

Proves regularity of extremal function on compact Kähler manifolds.

problem Regularity of extremal function on compact Kähler manifolds.
method Local property analysis and equivalence of continuity and Hölder continuity.
result Equivalence of classical notions of local LL-regularity and locally Hölder continuous property.

LLE produces unwanted results without regularization, which can be prevented with regularization.

problem LLE's inherent unwanted results without regularization.
method Mathematical proof and numerical examples of regularization effectiveness.
result Regularization prevents unwanted results in LLE.

Sharp bounds on diameter and eigenvalues for amply regular graphs.

problem Finding bounds for amply regular graphs' diameter and eigenvalues.
method New ideas relating discrete Ricci curvature to local matching properties, including a novel construction of a regular bipartite graph.
result Sharp diameter and eigenvalue bounds for amply regular graphs.

The paper explains implicit regularization in hierarchical tensor factorization and deep CNNs.

problem Understanding implicit regularization in complex neural network architectures.
method Theoretical analysis using dynamical systems to overcome challenges in hierarchy.
result Established implicit regularization towards low hierarchical tensor rank, equivalent to locality in CNNs.

We prove the existence of the flow by curvature of regular planar networks starting from an initial network which is non-regular. The proof relies on a monotonicity formula for expanding solutions and a local regularity result for the network flow in the spirit of B. White's local regularity theorem for mean curvature …

2014-07-17abs ↗pdf ↗

A new algorithm speeds up EEG source localization using 1\ell_1 regularization.

problem Challenging inverse problem in mapping EEG readings to brain activity.
method Formulated as a graphical generalized elastic net inverse problem, solved with a variable projected algorithm (VPAL).
result VPAL provides faster and more accurate EEG source localization compared to existing methods.

Locality regularized reconstruction finds sparse coefficients for sparse and structured data.

problem Finding sparse coefficients for linear representations of data.
method Solves a regularized least squares regression problem with a locality function promoting use of columns close to the target vector.
result Optimal coefficients have at most d+1d+1 non-zero entries, and can be supported on the vertices of the Delaunay simplex.

Classifies local boundary conditions for Dirac-type operators on manifolds.

problem Determining all local smooth boundary conditions for Dirac-type operators.
method Combining general theory of boundary value problems for Dirac operators and pointwise considerations.
result Classification of local self-adjoint regular boundary conditions for Dirac spinors in dimensions 3 and 4.

Consider an integral Brakke flow (μt)(μ_t), t[0,T]t\in [0,T], inside some ball in Euclidean space. If μ0μ_{0} has small height, its measure does not deviate too much from that of a plane and if μTμ_{T} is non-empty, then Brakke's local regularity theorem yields that (μt)(μ_t) is actually smooth and graphical inside a smaller b…

2016-01-25abs ↗pdf ↗

One of the main strengths of online algorithms is their ability to adapt to arbitrary data sequences. This is especially important in nonparametric settings, where performance is measured against rich classes of comparator functions that are able to fit complex environments. Although such hard comparators and complex e…

2020-02-05abs ↗pdf ↗

Recent advances in deep learning theory have evoked the study of generalizability across different local minima of deep neural networks (DNNs). While current work focused on either discovering properties of good local minima or developing regularization techniques to induce good local minima, no approach exists that ca…

2019-11-19abs ↗pdf ↗

Efficient regularization mitigates catastrophic overfitting in single-step adversarial training.

problem Catastrophic overfitting in single-step adversarial training.
method ELLE regularization term to enforce local linearity of the loss function.
result Our regularization term effectively mitigates catastrophic overfitting without the drawbacks of previous methods.

DiCE uses diverse agents to explore and learn, avoiding local minima.

problem Local minima in RL due to limited exploration and correlated behavior.
method DiCE employs a group of heterogeneous agents to explore simultaneously and share experiences, with a diversity regularization mechanism.
result DiCE achieves substantial improvement over baselines in MuJoCo locomotion tasks.

We present a reduction procedure for locally conformally symplectic (LCS) manifolds with an action of a Lie group preserving the conformal structure, with respect to any regular value of the momentum mapping. Under certain conditions, this reduction is compatible with the existence of a locally conformally Kähler struc…

2018-08-31abs ↗pdf ↗

We compute approximate solutions to L0 regularized linear regression using L1 regularization, also known as the Lasso, as an initialization step. Our algorithm, the Lass-0 ("Lass-zero"), uses a computationally efficient stepwise search to determine a locally optimal L0 solution given any L1 regularization solution. We …

2015-11-13abs ↗pdf ↗

In this article we introduce local gauge conditions under which many curvature tensors appearing in conformal geometry, such as the Weyl, Cotton, Bach, and Fefferman-Graham obstruction tensors, become elliptic operators. The gauge conditions amount to fixing an nn-harmonic coordinate system and normalizing the determi…

2013-10-14abs ↗pdf ↗

CurvSSL improves SSL by aligning local manifold curvature.

problem Improving self-supervised learning by capturing local manifold geometry.
method CurvSSL augments Barlow Twins with a curvature-based regularizer to align and decorrelate embeddings across augmentations.
result Curvature-regularized SSL yields competitive or improved linear evaluation performance.

We investigate the local regularity of pointed spacetimes, that is, time-oriented Lorentzian manifolds in which a point and a future-oriented, unit timelike vector (an observer) are selected. Our main result covers the class of Einstein vacuum spacetimes. Under curvature and injectivity bounds only, we establish the ex…

2008-12-30abs ↗pdf ↗

The abstract proves the existence and regularity of Brakke flows starting from a given set.

problem Existence and regularity of Brakke flows starting from a given set.
method Proves the existence and regularity of Brakke flows using a closed countably 1-rectifiable set in R^2.
result For almost all time, the flow locally consists of a finite number of embedded curves of class W^{2,2} whose endpoints meet at junctions with angles of 0, 60, or 120 degrees.

FedElasticNet reduces communication costs and handles client drift in FL.

problem Expensive communication costs and client drift issues in federated learning.
method Leverages elastic net regularizers to sparsify local updates and limit client drift.
result FedElasticNet effectively resolves communication cost and client drift problems.

A regular F-manifold is an F-manifold (with Euler field) (M, \circ, e, E), such that the endomorphism {\mathcal U}(X) := E \circ X of TM is regular at any p\in M. We prove that the germ ((M,p), \circ, e, E) is uniquely determined (up to isomorphism) by the conjugacy class of {\mathcal U}_{p} : T_{p}M \rightarrow T_{p}M…

2014-11-17abs ↗pdf ↗

The study extends convergence theorems for Ricci-limit spaces with bounded curvature.

problem Understanding convergence properties of Ricci-limit spaces with bounded curvature.
method Establishing C1,αC^{1,α}-regularities and applying Fukaya's fibration theorem.
result Optimal generalization of Fukaya's fibration theorem to C1,αC^{1,α} limit spaces.

Existence of calibrated local stochastic volatility models proven for non-regular coefficients.

problem Existence of calibrated local stochastic volatility models in finance.
method Investigation of McKean--Vlasov equations with minimal continuity assumptions on coefficients, providing existence and propagation of chaos results.
result Existence of calibrated local stochastic volatility models for appropriate stochastic volatility parameters.

Regression is an important task in machine learning and data mining. It has several applications in various domains, including finance, biomedical, and computer vision. Recently, network Lasso, which estimates local models by making clusters using the network information, was proposed and its superior performance was d…

2020-02-21abs ↗pdf ↗

We show the local wellposedness of biharmonic wave maps with initial data of sufficiently high Sobolev regularity and a blow-up criterion in the sup-norm of the gradient of the solutions. In contrast to the wave maps equation we use a vanishing viscosity argument and an appropriate parabolic regularization in order to …

2019-03-05abs ↗pdf ↗

Develops local elliptic regularity for geometrically-natural operators with low regularity coefficients.

problem Local elliptic regularity for operators with low regularity coefficients in Sobolev-type spaces.
method Rescaling estimates and multiplication results for function spaces.
result Unified set of interior estimates and regularity inference for operators with Sobolev-type coefficients.

The paper improves SVM and localized SVM stability under triple perturbations.

problem Stability of SVMs and localized SVMs under triple perturbations.
method Generalizes and improves existing results, considering simultaneous variations in probability measure, regularization parameter, and kernel.
result Improved stability of SVMs and localized SVMs under triple perturbations.