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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.

168,786 papers · 148 categories

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90180270360 · Jun 202019922001200920172026
48 results for higher regularity

Develops higher arity VC theory and characterizes PAC learning in product spaces.

problem Characterizing PAC learning in multi-dimensional product spaces.
method Introduces higher arity VC dimension, generalizes Haussler packing lemma, and develops hypergraph regularity lemma.
result Characterizes higher arity PAC learning in n-fold product spaces.

Paper explores weak solutions' regularity in critical dimensions without conservation law.

problem Regularity of weak solutions to higher order elliptic systems in critical dimensions.
method Elementary and unified treatment, without conservation law.
result Interior Hölder continuity for solutions in critical dimensions.

State-of-the-art methods in convex and non-convex optimization employ higher-order derivative information, either implicitly or explicitly. We explore the limitations of higher-order optimization and prove that even for convex optimization, a polynomial dependence on the approximation guarantee and higher-order smoothn…

2017-10-27abs ↗pdf ↗

Dropout regularizes against high-order interactions by canceling interaction rates.

problem Overfitting to high-order interactions in neural networks.
method Analyzes Dropout through the lens of interaction effects, showing how it effectively cancels out the probability of surviving interactions of different orders.
result Dropout regularizes against high-order interactions by effectively canceling out the probability of surviving interactions of different orders.

This lecture notes are an expanded version of the course given at the ERC-School on Geometric Measure Theory and Real Analysis, held in Pisa, September 30th - October 30th 2013. The lectures aim to explain the main steps of a new proof of the partial regularity of area minimizing integer rectifiable currents in higher …

2015-01-15abs ↗pdf ↗

We introduce a regularization method for mean curvature flow of a submanifold of arbitrary codimension in the Euclidean space, through higher order equations. We prove that the regularized problems converge to the mean curvature flow for all times before the first singularity.

2004-07-19abs ↗pdf ↗

The purpose of this article is to present a new regularization technique of quasi-plurisubharmoinc functions on a compact Kaehler manifold. The idea is to regularize the function on local coordinate balls first, and then glue each piece together. Therefore, all the higher order terms in the complex Hessian of this regu…

2017-05-20abs ↗pdf ↗

In [Cheeger-Tian 2005], Cheeger-Tian proved an εε-regularity theorem for 44-dimensional Einstein manifolds without volume assumption. They conjectured that similar results should hold for critical metrics with constant scalar curvature, shrinking Ricci solitons, Ricci flows in 44-dimensional manifolds and higher dim…

2017-07-18abs ↗pdf ↗

Study shows how optimal transport behaves in higher dimensions.

problem Characterizing optimal transport in higher dimensions with Euclidean distance.
method Investigates the small regularization limit of entropic optimal transport.
result The limiting transport plan is supported on transport rays and uniquely minimizes a relative entropy functional.

Improved optimal regularity for harmonic almost complex structures.

problem Establishing optimal regularity for harmonic almost complex structures.
method Quantitative stratification method and rectifiability of singular strata.
result Optimal regularity theory for energy minimizing harmonic almost complex structures.

Existence of harmonic maps from higher-dimensional manifolds to spheres proven.

problem Proving existence of nonconstant harmonic maps from arbitrary manifolds to spheres.
method Using optimal regularity and eigenvalue optimization on manifolds.
result First general existence result for harmonic maps from higher-dimensional manifolds to a large class of positively curved targets.

The paper constructs new non-trivial harmonic maps into higher-dimensional target manifolds.

problem Existence of non-trivial harmonic maps into higher-dimensional target manifolds.
method Perturbative argument, refined neck-analysis, energy identity, min-max problems.
result Construction of an infinite family of new null-homotopic nn-harmonic nn-spheres.

New models for short rates show longer periods at higher rates.

problem Modeling longer periods of higher interest rates.
method Developed a class of time-homogeneous one-factor Markov diffusion models with specific boundary conditions.
result Explicit expressions for bond prices and transition densities in new probability measure.

The p-Laplacian Transformer improves transformer models by assigning higher attention weights to tokens in close proximity.

problem The self-attention mechanism in transformers does not effectively distinguish attention weights between tokens in close and non-close proximity.
method Proposes a novel class of transformers, p-Laplacian Transformers, that use pp-Laplacian regularization to assign higher attention weights to tokens in close proximity.
result Empirically demonstrates that p-Laplacian Transformers outperform baseline transformers on various benchmark datasets.

Users form information trails as they browse the web, checkin with a geolocation, rate items, or consume media. A common problem is to predict what a user might do next for the purposes of guidance, recommendation, or prefetching. First-order and higher-order Markov chains have been widely used methods to study such se…

2017-04-20abs ↗pdf ↗

This paper examines how Higher-Order Langevin Dynamics reduces memorization in diffusion models.

problem Memorization of training samples in diffusion models, violating copyright and privacy.
method Introduces Higher-Order Langevin Dynamics (HOLD) to regularize diffusion model trajectories.
result The dynamics of the data variable in HOLD are governed by a low-pass-filtered version of the learned score function, with smoothness increasing with model order.

Designs a neural network to reduce training cost by mapping to higher dimensions.

problem High training cost in neural networks.
method Maps feature vectors to higher dimensional space, designs weight matrices to reduce cost, uses convex constraints.
result Reduces training cost as the number of layers increases, without cross-validation.

We show that degenerate horizons exhibit a new trapping effect. Specifically, we obtain a non-degenerate Morawetz estimate for the wave equation in the domain of outer communications of extremal Reissner-Nordstrom up to and including the future event horizon. We show that such an estimate requires 1) a higher degree of…

2015-12-30abs ↗pdf ↗

Cross validation (CV) and the bootstrap are ubiquitous model-agnostic tools for assessing the error or variability of machine learning and statistical estimators. However, these methods require repeatedly re-fitting the model with different weighted versions of the original dataset, which can be prohibitively time-cons…

2019-07-28abs ↗pdf ↗

Given a closed submanifold, or a compact regular domain, in euclidean space, we consider the Riesz energy defined as the double integral of some power of the distance between pairs of points. When this integral diverges, we compare two different regularization techniques (Hadamard's finite part and analytic continuatio…

2015-12-25abs ↗pdf ↗

Mean curvature flow of clusters of n-dimensional surfaces in R^{n+k} that meet in triples at equal angles along smooth edges and higher order junctions on lower dimensional faces is a natural extension of classical mean curvature flow. We call such a flow a mean curvature flow with triple edges. We show that if a smoot…

2016-05-21abs ↗pdf ↗

We study primitive stable representations of free groups into higher rank semisimple Lie groups and their properties. Let ΣΣ be a compact, connected, orientable surface (possibly with boundary) of negative Euler characteristic. We first verify the σmodσ_{mod}-regularity for convex projective structures and positive repr…

2015-04-30abs ↗pdf ↗

We study the existence and properties of metrics maximising the first Laplace eigenvalue among conformal metrics of unit volume on Riemannian surfaces. We describe a general approach to this problem and its higher eigenvalue versions via the direct method of calculus of variations. The principal results include the gen…

2011-03-12abs ↗pdf ↗

FedLoRU improves FL efficiency by using low-rank updates.

problem Communication inefficiency and performance reduction in Federated Learning.
method Proposes FedLoRU, a low-rank update framework for FL, which reduces communication costs while maintaining performance.
result FedLoRU achieves convergence rates similar to FedAvg and is robust to heterogeneous and large numbers of clients.

We develop a new approach, based on quantization methods, to study higher symmetries of invariant differential operators. We focus here on conformally invariant powers of the Laplacian over a conformally flat manifold and recover results of Eastwood, Leistner, Gover and Šilhan. In particular, conformally equivariant qu…

2011-07-28abs ↗pdf ↗