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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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4489133177 · Jun 202019922001200920172026
48 results for order-preserving maps

In this paper we further investigate the geometry of monads of order-preserving functionals and of positively homogeneous functionals. We prove that for any compactum X with w(X)=τw(X) = τ the map μFXμ_F X, where F{O,OH}F\in\{O,OH\}, is homeomorphic to trivial IτI^τ-fibration if and only if XX is openly generated χχ-homogeneou…

2010-05-31abs ↗pdf ↗

In this article we introduce order preserving representations of fundamental groups of surfaces into Lie groups with bi-invariant orders. By relating order preserving representations to weakly maximal representations, introduced in arXiv:1305.2620, we show that order preserving representations into Lie groups of Hermit…

2016-01-10abs ↗pdf ↗

OP-GFNs sample candidates in order-preserving proportion to a learned reward function.

problem Sampling diverse candidates with varying rewards in multi-objective optimization.
method Order-Preserving GFlowNets (OP-GFNs) use a learned reward function consistent with a provided order on candidates.
result Training OP-GFNs sparsifies the reward landscape, focusing on higher-ranked candidates.

A new method estimates rare events using tensor trains.

problem Estimating rare event probabilities in high-dimensional problems.
method Approximating optimal importance distribution via tensor-train decompositions and compositions.
result Better variance reduction and efficient computation of rare event probabilities.

We present a novel factor analysis method that can be applied to the discovery of common factors shared among trajectories in multivariate time series data. These factors satisfy a precedence-ordering property: certain factors are recruited only after some other factors are activated. Precedence-ordering arise in appli…

2011-05-09abs ↗pdf ↗

Enhances image classification by integrating semantic hierarchy into CNN models.

problem Limited use of external guidance in image classification.
method Integrates label-hierarchy knowledge into CNN-based classifiers and uses order-preserving embeddings.
result Boosts image classification performance through semantic hierarchy integration.

New set class preserves Fourier series terms for planar ovals, leading to isoperimetric inequalities.

problem Investigate geometric properties of kkth Order Preserving Sets and ovals.
method Introduce and analyze kkth Order Preserving Sets and Midpoint Sets; study geometric properties and isoperimetric inequalities.
result Established an isoperimetric-type inequality relating perimeter and area of ovals and their associated sets.

The thesis introduces methods to use semantic hierarchy in image classification.

problem Limited work in training image classifiers with non-conventional external guidance.
method Injects label hierarchy knowledge into arbitrary classifiers and uses order-preserving embeddings for image classification.
result Both embedding-based models and CNN-classifiers with hierarchical information outperform a hierarchy-agnostic model.

MCNet improves uncertainty calibration in online advertising by modeling complex relations and balancing performance.

problem Lack of effective calibration for complex relations and context features in online advertising.
method Introduces MCNet with MCF, order-preserving, and field-balance regularizers.
result Superior performance in generating well-calibrated probability predictions on public and industrial datasets.

Efficiently learns and transports posterior densities for real-time inference.

problem High computational cost of Bayesian inference for complex posterior densities.
method Tensor-train (TT) format for offline learning, conditional transport for online inference.
result Significant improvement in inference performance for high-dimensional problems.

Framework analyzes neural network dynamics for better understanding and optimization.

problem Understanding the fundamental mechanisms of deep neural networks.
method Dynamical systems theory, transformation units, attraction basins.
result Different transformation modes lead to distinct learning phases and network performance.

Paper generalizes tensor-train approximation for complex random variables.

problem Characterizing intractable high-dimensional random variables.
method Extends inverse Rosenblatt transform to general reference measures and integrates into deep variable transformation framework.
result Deep inverse Rosenblatt transport significantly expands tensor approximations for complex random variables.

It is well known that a countable group admits a left-invariant total order if and only if it acts faithfully on R by orientation preserving homeomorphisms. Such group actions are special cases of group actions on simply connected 1-manifolds, or equivalently, actions on oriented order trees. We characterize a class of…

2005-03-21abs ↗pdf ↗

Let (W,S) be a finite rank Coxeter system with W infinite. We prove that the limit weak order on the blocks of infinite reduced words of W is encoded by the topology of the Tits boundary of the Davis complex X of W. We consider many special cases, including W word hyperbolic, and X with isolated flats. We establish tha…

2013-01-05abs ↗pdf ↗

It is well-known that there is a faithful representation of braid groups on automorphism groups of free groups, and it is also well-known that free groups are bi-orderable. We investigate which n-strand braids give rise to automorphisms which preserve some bi-ordering of the free group rank n. As a consequence of our w…

2016-10-11abs ↗pdf ↗

The paper develops a Galois theory for cluster algebras and Riemann surfaces.

problem Building a correspondence between cluster subalgebras and automorphism groups.
method Introducing Galois-like extensions and automorphism groups for cluster algebras.
result Conditions for Galois-like extensions and properties of cluster automorphism groups.

A lot of attention has been devoted to multimedia indexing over the past few years. In the literature, we often consider two kinds of fusion schemes: The early fusion and the late fusion. In this paper we focus on late classifier fusion, where one combines the scores of each modality at the decision level. To tackle th…

2012-07-04abs ↗pdf ↗

In the past few years, a lot of attention has been devoted to multimedia indexing by fusing multimodal informations. Two kinds of fusion schemes are generally considered: The early fusion and the late fusion. We focus on late classifier fusion, where one combines the scores of each modality at the decision level. To ta…

2014-04-30abs ↗pdf ↗

Paper finds formulas for mutual information and MMSE in matrix tensor product problems.

problem High-dimensional inference problems involving matrix tensor products.
method Single-letter formulas for mutual information and MMSE, using new techniques.
result Analytical formulas describe leading order terms in mutual information and MMSE.

A new framework separates classifier calibration and discrimination.

problem Combining reliability and resolution in probabilistic predictions.
method Manokhin Probability Matrix separates reliability and resolution using Spiegelhalter Z-statistic and AUC-ROC.
result Classifiers are categorized into four archetypes: Eagle, Bull, Sloth, and Mole.

Develops a new nonparametric trace regression model for high-dimensional data.

problem Violation of known functional form and global low-rank structure assumptions in trace regression.
method Structured sign series representations for nonparametric trace regression models.
result Establishes excess risk bounds and sample complexities for the proposed model.

Maps are an important medium that enable people to comprehensively understand the configuration of cultural activities and natural elements over different times and places. Although massive maps are available in the digital era, how to effectively and accurately access the required map remains a challenge today. Previo…

2018-05-26abs ↗pdf ↗

Both bi-harmonic map and ff-harmonic map have nice physical motivation and applications. In this paper, by combination of these two harmonic maps, we introduce and study ff-bi-harmonic maps as the critical points of the ff-bi-energy functional 12Mfτ(φ)2dvg\frac{1}{2}\int_M f|τ(φ)|^2dv_{g}. This class of maps generalizes both …

2013-05-23abs ↗pdf ↗

Research explores real algebraic realization of round fold maps of codimension -1.

problem Real algebraic realization of round fold maps of codimension -1.
method Generalizes canonical projections of unit spheres to round fold maps and discusses their real algebraic realization.
result Developed new studies in real algebraic geometry focusing on round fold maps of codimension -1.

The paper derives Liouville theorems for various generalized maps on Riemannian manifolds.

problem Deriving Liouville theorems for generalized maps on Riemannian manifolds.
method Using conservation laws and monotonicity formulas, the paper derives Liouville theorems for different types of maps under various conditions.
result The paper establishes Liouville theorems for several types of generalized maps, including φφ-FF harmonic maps, φφ-FF symphonic maps, and φφ-FF-VV-harmonic maps.

The paper explores unique continuation properties for polyharmonic maps between Riemannian manifolds.

problem Investigating unique continuation principles for polyharmonic maps.
method Analyzing critical points of higher order functionals to prove extensions of known results in harmonic and biharmonic cases.
result Proving extensions of unique continuation principles for k-harmonic maps.

The hyperelliptic mapping class group has been studied in various contexts within topology and algebraic geometry. What makes this study tractable is that there is a surjective map from the hyperelliptic mapping class group to a mapping class group of a punctured sphere. The more general family of superelliptic mapping…

2016-04-13abs ↗pdf ↗

This paper constructs real algebraic maps that are topologically special generic maps.

problem Constructing smooth maps in differential topology and real algebraic geometry.
method Constructs real algebraic maps that are topologically special generic maps.
result Real algebraic maps are topologically special generic maps.

Characterizes a general range decreasing group homomorphism.

problem Understanding range decreasing group homomorphisms in the entire mapping group.
method Characterization of a general range decreasing group homomorphism.
result Computes a particular class of homomorphisms and identifies all range decreasing group homomorphisms on specific mapping groups.