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.
The paper constructs a Dirichlet form and proves functional inequalities for a specific measure.
Random matrix ensembles yield uniform distributions on manifolds.
GBEST model improves survival analysis for small datasets.
This work improves distribution recovery from sparse data using Random Forest implicit regularization.
New solutions found for elliptic sinh-Gordon and sine-Gordon equations.
Study on sine-cones' spectra and stability under Ricci-de Turck flow.
Sine activation functions enable two-layer neural networks to learn modular addition more efficiently.
FDN improves probabilistic regressors' adaptability to distribution shifts.
Guichard's transformations generate Voss surfaces from sine-Gordon solutions.
Formulae for Bäcklund transformations of hyperbolic and elliptic sine-Gordon/sinh-Gordon equations.
Vote-boosting is a sequential ensemble learning method in which the individual classifiers are built on different weighted versions of the training data. To build a new classifier, the weight of each training instance is determined in terms of the degree of disagreement among the current ensemble predictions for that i…
Derives hyperbolic laws of cosines and sines with fermionic corrections.
Extreme learning machine (ELM) as a neural network algorithm has shown its good performance, such as fast speed, simple structure etc, but also, weak robustness is an unavoidable defect in original ELM for blended data. We present a new machine learning framework called LARSEN-ELM for overcoming this problem. In our pa…
Sharp isoperimetric inequalities for the sine transform of even isotropic measures are established. The corresponding reverse inequalities are obtained in an asymptotically optimal form. These new inequalities have direct applications to strong volume estimates for convex bodies from data about their sections or projec…
For many applications, an ensemble of base classifiers is an effective solution. The tuning of its parameters(number of classes, amount of data on which each classifier is to be trained on, etc.) requires G, the generalization error of a given ensemble. The efficient estimation of G is the focus of this paper. The key …
Proposes a new factor to improve BAB strategies by recognizing bad-beta assets.
New f-Betas for portfolio optimization using f-divergence risk measures.
Hybrid ML ensemble predicts market risk and generates alpha.
In trying to provide explicit deformations of quadrics the starting point of our investigation is to use Bianchi's link between real deformations of totally real regions of real paraboloids and various totally real forms of the sine-Gordon equation coupled with Bianchi's simple observation that the vacuum soliton of th…
Study examines time-varying betas and their volatility in bank interest income and expense margins.
We study relations of the Weierstrass's hyperelliptic al-functions over a non-degenerated hyperelliptic curve of arbitrary genus as solutions of sine-Gordon equation using Weierstrass's local parameters, which are characterized by two ramified points. Though the hyperelliptic solutions of the sine-Gord…
In this paper, we consider the discrete deformation of the discrete space curves with constant torsion described by the discrete mKdV or the discrete sine-Gordon equations, and show that it is formulated as the torsion-preserving equidistant deformation on the osculating plane which satisfies the isoperimetric conditio…
Proposes logistic-beta process for modeling dependent probabilities with beta marginals.
Machine learning improves beta forecasts, enhancing equity valuation and portfolio performance.
We present a unified method of construction of surfaces associated with Grassmannian sigma models, expressed in terms of an orthogonal projector. This description leads to compact formulae for structural equations of two-dimensional surfaces immersed in the su(N) algebra. In the special case of the CP^1 sigma model we …
Unified study of harmonic maps between pseudo-Riemannian surfaces.
Twisted - and twisted -hierarchies are soliton hierarchies introduced by Terng to find higher flows of the generalized sine-Gordon equation. Twisted -hierarchies are among the most important classes of twisted hierarchies. In this paper, interesting first and higher flows of twi…
A beta-negative binomial (BNB) process is proposed, leading to a beta-gamma-Poisson process, which may be viewed as a "multi-scoop" generalization of the beta-Bernoulli process. The BNB process is augmented into a beta-gamma-gamma-Poisson hierarchical structure, and applied as a nonparametric Bayesian prior for an infi…
The beta-Bernoulli process provides a Bayesian nonparametric prior for models involving collections of binary-valued features. A draw from the beta process yields an infinite collection of probabilities in the unit interval, and a draw from the Bernoulli process turns these into binary-valued features. Recent work has …
Beta diffusion generates bounded data using multiplicative transitions.
We show that the stick-breaking construction of the beta process due to Paisley, et al. (2010) can be obtained from the characterization of the beta process as a Poisson process. Specifically, we show that the mean measure of the underlying Poisson process is equal to that of the beta process. We use this underlying re…
A novel SVR parameter optimization method using GSA outperforms other meta-heuristics in stock market forecasting.
In this paper, the geometric meaning of (alpha,beta)-norms is made clear. On this basis, we introduce a new class of Finsler metrics called general (alpha,beta)-metrics, which are defined by a Riemannian metric and an 1-form. These metrics not only generalize original (alpha,beta)-metrics naturally, but also include so…
Study beta function for convex billiard maps, linking spectral invariants.
FMMNN combines sine activations with multi-component, multi-layer structure for high-frequency function approximation.
New harmonic maps to hyperbolic plane via Bäcklund transformation.
Beta-SOD detects and corrects noisy object re-identification using cosine similarity and Beta mixtures.
We present a reactive beta model that includes the leverage effect to allow hedge fund managers to target a near-zero beta for market neutral strategies. For this purpose, we derive a metric of correlation with leverage effect to identify the relation between the market beta and volatility changes. An empirical test ba…
This is a short description of graphic lambda calculus, with special emphasis on a duality suggested by the two different appearances of knot diagrams, in lambda calculus and emergent algebra sectors of the graphic lambda calculus respectively. This duality leads to the introduction of the dual of the graphic beta move…
Bayesian Beta regression for proportions in high dimensions with theoretical guarantees.
NeuralBeta uses deep learning to estimate beta, outperforming traditional methods.
We describe the underlying probabilistic interpretation of alpha and beta divergences. We first show that beta divergences are inherently tied to Tweedie distributions, a particular type of exponential family, known as exponential dispersion models. Starting from the variance function of a Tweedie model, we outline how…
Study explores geometric structure and prior for beta-logistic distribution.
A well-constructed classification model highly depends on input feature subsets from a dataset, which may contain redundant, irrelevant, or noisy features. This challenge can be worse while dealing with medical datasets. The main aim of feature selection as a pre-processing task is to eliminate these features and selec…
The paper proves optimizability implies inequalities for sampling.
Unified framework for scale-invariant representation learning using MAPCA.
In this paper we continue investigation of the constant astigmatism equation z_{yy} + (1/z)_{xx} + 2 = 0. We newly interpret its solutions as describing spherical orthogonal equiareal patterns, with relevance to two-dimensional plasticity. We show how the classical Bianchi superposition principle for the sine-Gordon eq…
This paper generalizes beta divergence beyond its classical form associated with power variance functions of Tweedie models. Generalized form is represented by a compact definite integral as a function of variance function of the exponential dispersion model. This compact integral form simplifies derivations of many pr…