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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.

169,236 papers · 148 categories

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101201302402 · Jun 202019922001200920182026
48 results for differential similarity

The paper extends differential similarity theory to higher dimensions and develops algorithms for clustering and coding.

problem Developing algorithms for clustering and coding in higher-dimensional spaces.
method Combines geometric and probabilistic models in nn-dimensional space, focusing on strategies for computation and parameter estimation.
result Evaluates solution strategies and estimation techniques using MNIST and CIFAR-10 datasets.

It is known that the long line supports 212^{\aleph_1} many non-diffeomorphic differential structures. We show that the long plane supports a similar number of exotic differential structures, ie structures which are not merely diffeomorphic to the product of two structures on the factor spaces.

2012-11-20abs ↗pdf ↗

Improved efficient learning of neighbor representations for large datasets.

problem Efficiently learn neighbor representations for large datasets.
method Differentiable Boundary Sets algorithm that overcomes computational issues and improves accuracy.
result Significant reduction in training time and improved classification accuracy.

Generalizes Black-Scholes model for option pricing under uncertainty.

problem Traditional Black-Scholes model for option pricing under uncertainty.
method Generalized Black-Scholes model using non-symmetric Dirichlet forms and abstract PDE theory.
result Well-posedness of the generalized model established.

Let τ ⁣:E~Eτ\colon\tilde{\mathcal{E}}\to\mathcal{E} be a differential covering of a PDE E~\tilde{\mathcal{E}} over E\mathcal{E}. We prove that if E\mathcal{E} possesses infinite number of symmetries and/or conservation laws then E~\tilde{\mathcal{E}} has similar properties.

2013-10-04abs ↗pdf ↗

A new method matches similar regions in non-rigid shapes using spectra of differential operators.

problem Evaluating similarity of non-rigid shapes with partiality.
method Alignment of spectra of differential operators (SI-LBO and regular LBO) on a manifold with multiple metrics.
result Matching spectra outperforms competing methods on standard benchmarks.

We give a full description of Darboux transformations of any order for arbitrary (nondegenerate) differential operators on the superline. We show that every Darboux transformation of such operators factorizes into elementary Darboux transformations of order one. Similar statement holds for operators on the ordinary lin…

2015-05-19abs ↗pdf ↗

Introduces CHL, a new loss function for continuous similarity learning.

problem Binary similarity learning limitations.
method CHL is a novel loss function that generalizes histogram loss to continuous similarities.
result CHL solves a wider range of tasks including similarity learning, representation learning, and data visualization.

PGFL framework learns personalized models with differential privacy.

problem Privacy-preserving personalized learning for diverse data.
method Exploits model similarities and differential privacy (zero-concentrated).
result Algorithm converges to optimal solutions with linear time complexity.

Gradient-based method extracts slow features from high-dimensional data.

problem Extracting meaningful low-dimensional features from high-dimensional, temporally varying data.
method Power Slow Feature Analysis (PowerSFA) using gradient-based training of differentiable architectures.
result PowerSFA effectively extracts meaningful low-dimensional features in various data types.

New method replaces traditional convex integration for solving geometric problems.

problem Constructing solutions with self-similarity properties in geometric embeddings.
method Introducing Kuiper differential relations and a Corrugation Process to replace traditional convex integration.
result Totally real isometric embeddings exhibit self-similarity and can be uniformly expressed.

Improved text generation using transferable rewards from related tasks.

problem Non-differentiable task-specific scores limit the use of policy gradient methods in text generation.
method Transferable Reward Learner that uses model-based rewards for sentence-level and phrase-level similarity.
result Improved performance on semantic evaluation measures in image captioning tasks.

The paper examines how to test if two learning algorithms produce similar outcomes.

problem Testing if two learning algorithms produce similar outcomes when trained on different data sets.
method Using Total Variation (TV) distance to measure similarity of posterior distributions.
result TV indistinguishable learning rules are equivalent to existing stability notions and can be statistically amplified.

The paper is devoted to differential geometric invariants determining a Frenet curve in up to a direct similarity These invariants can be presented by the Euclidean curvatures in terms of an arc lengths of the spherical indicatrices. Then, these invariants expressed by focal curvatures of the curve. And then, we give t…

2014-03-31abs ↗pdf ↗

The paper estimates eigenvalues for specific differential operators on curved spaces.

problem Estimating eigenvalues for a class of elliptic differential operators on Riemannian manifolds.
method Analyzes eigenvalue estimates for a broader class of elliptic differential operators in divergence form.
result Provides eigenvalue estimates for Gaussian shrinking solitons and specific domains.

We consider a fourth order partial differential equation in n-dimensional space introduced by Abreu in the context of Kähler metrics on toric orbifolds. Similarity solutions depending only on the radial coordinate in R^n are determined in terms of a second order ordinary differential equation. A local asymptotic analys…

2002-09-11abs ↗pdf ↗

Differential forms on the Fréchet manifold F(S,M) of smooth functions on a compact k-dimensional manifold S can be obtained in a natural way from pairs of differential forms on M and S by the hat pairing. Special cases are the transgression map associating (p-k)-forms on F(S,M) to p-forms on M (hat pairing with a const…

2011-11-16abs ↗pdf ↗

We review some recent results on the mean curvature flows of Lagrangian submanifolds from the perspective of geometric partial differential equations. These include global existence and convergence results, characterizations of first-time singularities, and constructions of self-similar solutions.

2011-04-17abs ↗pdf ↗

This paper explains differential privacy through hypothesis testing and analyzes its relaxations.

problem Understanding the hypothesis testing interpretation of differential privacy.
method Identifying conditions for a statistical divergence to satisfy a similar interpretation and analyzing relaxations of differential privacy based on Renyi divergence.
result Improved conversion rules between differential privacy and its relaxations based on Renyi divergence.

The paper introduces a method to improve adversarial robustness in neural networks using randomized perturbations.

problem Deep neural networks are sensitive to small perturbations on correctly classified examples, leading to erroneous predictions.
method The approach uses randomized perturbations to optimize the worst case loss function over all possible substitutions of training examples, ensuring that substitution likelihood is weighted by the proximity to the original word.
result The method achieves performance gains and differentially-private model training, improving robustness against adversarial attacks.

New method solves differential equations on manifolds, with applications in physics.

problem Solving differential equations on Riemannian manifolds.
method Developed linear homotopy theory for codifferential operator, leading to a direct sum decomposition of differential forms.
result Shows a new way to solve exterior differential systems, applicable to fundamental physics equations.

Proposes a new neural network for text-dependent speaker verification.

problem Improves speaker verification by encoding phrase and speaker information.
method Uses differentiable alignment models to produce supervectors from utterances.
result Achieves competitive performance in text-dependent speaker verification tasks.

A Lie algebroid over a manifold is a vector bundle over that manifold whose properties are very similar to those of a tangent bundle. Its dual bundle has properties very similar to those of a cotangent bundle: in the graded algebra of sections of its external powers, one can define an operator similar to the exterior d…

2008-04-15abs ↗pdf ↗

Let M be a complex nilmanifold, that is, a compact quotient of a nilpotent Lie group endowed with an invariant complex structure by a discrete lattice. A holomorphic differential on M is a closed, holomorphic 1-form. We show that a(M)ka(M)\leq k, where a(M)a(M) is the algebraic dimension a(M)a(M) (i.e. the transcendence degre…

2016-03-06abs ↗pdf ↗