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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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185369554738 · Jun 202019922001200920172026
48 results for implicit function theorem

Global implicit function theorem for Fréchet spaces, solving derivative loss problems.

problem Solving initial value problems with derivative loss in Fréchet spaces.
method Global implicit function theorems for Keller's Cc1C_c^1-mappings in Fréchet spaces, applied through submersions and transversality.
result Global existence and uniqueness of solutions to initial value problems with derivative loss.

A new method for optimizing non-decomposable metrics with constraints.

problem Optimizing complex machine learning objectives with thresholded constraints.
method Formulate rate-constrained optimization using the Implicit Function theorem and solve with gradient-based methods.
result Demonstrated effectiveness over existing methods on benchmark datasets.

New dual formulation reduces generalization error for ERM-fDR.

problem Generalization error in constrained optimization problems.
method Introduces a dual formulation of ERM-fDR using Legendre-Fenchel transform and implicit function theorem.
result Explicit characterizations of generalization error for algorithms under mild conditions.

The paper explores moduli space of heterotic system using two deformation paths.

problem Exploring the moduli space of the heterotic system.
method Considering two dual deformation paths starting from a Kähler solution, one along Bott-Chern cohomology class and the other along Aeppli cohomology class. Using the implicit function theorem to prove local existence of heterotic solutions.
result Established an initial step to construct local moduli coordinates around a Kähler solution.

Minimal surfaces with dihedral symmetry are studied as angles converge to zero.

problem Understanding minimal surfaces with dihedral symmetry as angles approach zero.
method Analyzing the limit of minimal surfaces in wedges with varying angles and using the implicit function theorem.
result New minimal surfaces are discovered and existence proofs are simplified.

Dual optimization connects ERM-fDR to normalization function.

problem Empirical risk minimization with f-divergence regularization.
method Dual formulation, Legendre-Fenchel transform, implicit function theorem, nonlinear ODE.
result Computational method to calculate normalization function efficiently.

Reduces function approximation dimensions from high to low with sparse data.

problem Function approximation from sparse data.
method Nonlinear Level Set Learning (NLL) with geometric information.
result Reduces input dimension to theoretical lower bound with minor accuracy loss.

We consider harmonic sections of a bundle over the complement of a codimension 2 submanifold in a Riemannian manifold, which can be thought of as multivalued harmonic functions. We prove a result to the effect that these are stable under small deformations of the data. The proof is an application of a version of the Na…

2019-12-17abs ↗pdf ↗

Paper constructs solutions to a system using Aeppli class without auxiliary gauge connection.

problem Constructing solutions to the Hull-Strominger system without auxiliary gauge connection.
method Deforming conformally balanced metric and tuning by Aeppli class to satisfy anomaly cancellation condition.
result Existence of family of solutions obtained via implicit function theorem.

We prove a version of the implicit function theorem for Lipschitz mappings f:Rn+mAXf:\mathbb{R}^{n+m}\supset A \to X into arbitrary metric spaces. As long as the pull-back of the Hausdorff content Hn\mathcal{H}_{\infty}^n by ff has positive upper nn-density on a set of positive Lebesgue measure, then, there is a local diff…

2018-09-18abs ↗pdf ↗

We establish a glueing theorem for the Ginzburg-Landau equations in dimension n>2n > 2. To this end, we consider a nondegenerate minimal submanifold of codimension 2, and construct a one-parameter family of solutions to the Ginzburg-Landau equations such that the energy density concentrates near this submanifold. The pr…

2003-02-06abs ↗pdf ↗

A geometric flow on (2,2)(2,2)-forms is introduced which preserves the balanced condition of metrics, and whose stationary points satisfy the anomaly equation in Strominger systems. The existence of solutions for a short time is established, using Hamilton's version of the Nash-Moser implicit function theorem.

2015-08-13abs ↗pdf ↗

Recently, there has been a growing interest in the problem of learning rich implicit models - those from which we can sample, but can not evaluate their density. These models apply some parametric function, such as a deep network, to a base measure, and are learned end-to-end using stochastic optimization. One strategy…

2017-09-04abs ↗pdf ↗

We propose an algorithm for inexpensive gradient-based hyperparameter optimization that combines the implicit function theorem (IFT) with efficient inverse Hessian approximations. We present results about the relationship between the IFT and differentiating through optimization, motivating our algorithm. We use the pro…

2019-11-06abs ↗pdf ↗

This is the revised version of the second paper in a series introducing a generalized Fredholm theory in a new class of smooth spaces called polyfolds. The theory will be illustrated in upcoming papers by applications to Floer Theory, Gromov-Witten Theory and Symplectic Field Theory. Some proofs have been improved and …

2007-05-09abs ↗pdf ↗

We establish continuous maximal regularity results for parabolic differential operators acting on sections of tensor bundles on Riemannian manifolds. As an application, we show that solutions to the Yamabe flow instantaneously regularize and become real analytic in space and time. The regularity result is obtained by i…

2013-09-09abs ↗pdf ↗

We will simplify earlier proofs of Perelman's collapsing theorem for 3-manifolds given by Shioya-Yamaguchi and Morgan-Tian. Among other things, we use Perelman's critical point theory (e.g., multiple conic singularity theory and his fibration theory) for Alexandrov spaces to construct the desired local Seifert fibratio…

2010-03-10abs ↗pdf ↗

For multi-valued functions---such as when the conditional distribution on targets given the inputs is multi-modal---standard regression approaches are not always desirable because they provide the conditional mean. Modal regression algorithms address this issue by instead finding the conditional mode(s). Most, however,…

2020-02-14abs ↗pdf ↗

The article studies deformations of Z2\mathbb Z_2-harmonic spinors on 3-manifolds.

problem Investigating the local structure of Z2\mathbb Z_2-harmonic spinors on 3-manifolds.
method Uses Nash-Moser Implicit Function Theorem to handle infinite-dimensional obstruction bundle and loss of regularity.
result Near a Z2\mathbb Z_2-harmonic spinor with smooth singular set, the universal moduli space projects to a codimension 1 submanifold.

In this paper, we prove the existence of maximal slices in anti-de Sitter spaces (ADS spaces) with small boundary data at spatial infinity. The main arguments is implicit function theorem. We also get a necessary and sufficient condition for boundary behavior of totally geodesic slice in ADS space. Moreover, we show th…

2006-09-11abs ↗pdf ↗

The paper constructs families of high genus CMC surfaces in the 3-sphere.

problem Existence and construction of high genus constant mean curvature surfaces.
method Implicit function theorem and iterative algorithm to compute power series expansions.
result Construction of complete and smooth families of CMC surfaces with increasing Willmore energy.

Research covers geometry, analysis, and integration on infinite-dimensional spaces.

problem Exploring geometric and analytical structures in infinite-dimensional settings.
method Analyzes numerical schemes, Lie groups, connections, and integration theory.
result Developed new methods for integration and analysis on infinite-dimensional manifolds.

The Gromoll-Meyer's generalized Morse lemma (so called splitting lemma) near degenerate critical points on Hilbert spaces, which is one of key results in infinite dimensional Morse theory, is usually stated for at least C2C^2-smooth functionals. It obstructs one using Morse theory to study most of variational problems …

2012-11-06abs ↗pdf ↗

Solves inverse problem for Maxwell equations using vector fields.

problem Inverse problem for Maxwell equations in vacuum.
method Abstract theory of implicit differential equations over pre-symplectic manifolds.
result Provides solution for Maxwell equations using vector fields.

We find necessary and sufficient conditions for a Lipschitz map f:REXf:\mathbb{R}E\to X, into a metric space to have the image with the kk-dimensional Hausdorff measure equal zero, Hk(f(E))=0H^k(f(E))=0. An interesting feature of our approach is that despite the fact that we are dealing with arbitrary metric spaces, we employ a …

2014-03-06abs ↗pdf ↗

EXODUS improves training of SNNs by stabilizing gradients and reducing complexity.

problem Training SNNs using BPTT is time-consuming and numerically unstable.
method EXODUS modifies SLAYER to account for neuron reset and uses IFT for correct gradient calculation, eliminating manual scaling.
result EXODUS achieves comparable or better performance than SLAYER, especially in tasks with temporal features.

New tensor formulation reveals gradient flow's bias in linear neural networks.

problem Understanding implicit bias in linear neural network training.
method Tensor formulation of neural networks, including fully-connected, diagonal, and convolutional networks.
result Gradient flow on linear tensor networks converges to solutions of specific optimization problems.

In this paper, we describe the "implicit autoencoder" (IAE), a generative autoencoder in which both the generative path and the recognition path are parametrized by implicit distributions. We use two generative adversarial networks to define the reconstruction and the regularization cost functions of the implicit autoe…

2018-05-24abs ↗pdf ↗

SINDy-PI robustly identifies implicit dynamics from noisy data.

problem Accurately modeling nonlinear dynamics from noisy data.
method Parallel, implicit SINDy algorithm with multiple optimization algorithms and model selection.
result Significantly more noise robust than previous SINDy approaches.