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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.

168,742 papers · 148 categories

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91183274365 · May 202619922001200920172026
48 results for local index density

Develops a new cluster validity index to find multiple optimal cluster numbers.

problem Finding the optimal number of clusters in real-world data with varying densities, sizes, and shapes.
method A new correlation-based cluster validity index that yields multiple local peaks.
result The new index finds multiple optimal cluster numbers in various scenarios.

One-pass private sketch supports various machine learning tasks.

problem Efficiently supporting multiple machine learning tasks with differential privacy.
method Randomized contingency tables indexed with locality-sensitive hashing, constructed in one pass.
result Competitive error bounds for DP kernel density estimation, faster than existing methods.

DIF extends NF with stochastic discrete latent variables for better density estimation.

problem Improving density estimation with discontinuities and fine details.
method Discretely indexed flows as an extension of Normalizing Flows with stochastic latent variables.
result DIF inherit good computational behavior of NF and can capture distributions with discontinuities.

For a smooth family F of admissible elliptic pseudodifferential operators with differential form coefficients associated to a geometric fibration of manifolds M--> B we show that there is a natural zeta-form z(F,s) and zeta-determinant- form det(F) in the de-Rham algebra of smooth differential forms, generalizing the c…

2004-06-15abs ↗pdf ↗

New findings confirm parallels to De Giorgi's conjecture for phase transitions in higher dimensions.

problem Understanding phase transitions with bounded index in higher-dimensional spaces.
method Establishing parallels to De Giorgi's conjecture for general solutions of bounded Morse index.
result Finite index solutions to the Allen--Cahn equation in R4\mathbb{R}^4 are one-dimensional, and this holds for all 4n74 \leq n \leq 7.

A new measure DCSI quantifies separability for density-based clustering.

problem Quantifying meaningful clusters in data sets.
method Developed a new separability measure DCSI based on separation and connectedness.
result Correctly identifies touching or overlapping classes that do not correspond to meaningful density-based clusters.

We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adaptive proposal density. The adaptive proposal density is assumed to be the Student's t-distribution and the distribution parameters are evaluated by using the data sampled during the simulation. We apply the method for th…

2009-08-20abs ↗pdf ↗

We compute the analytic expression of the probability distributions F{AEX,+} and F{AEX,-} of the normalized positive and negative AEX (Netherlands) index daily returns r(t). Furthermore, we define the αre-scaled AEX daily index positive returns r(t)^αand negative returns (-r(t))^αthat we call, after normalization, the …

2010-04-07abs ↗pdf ↗

This paper presents a simple but effective density-based outlier detection approach with the local kernel density estimation (KDE). A Relative Density-based Outlier Score (RDOS) is introduced to measure the local outlierness of objects, in which the density distribution at the location of an object is estimated with a …

2016-06-28abs ↗pdf ↗

EagleEye detects localized density anomalies in multivariate data.

problem Identifying signal events, regime changes, or model mismatch in scientific data.
method EagleEye pinpoints local over- and under-densities by assigning anomaly scores based on binary membership sequences and binomial null models.
result EagleEye can detect genuine local anomalies and estimate background purity.

We use an index-theoretic technique of Hitchin to show that the space of complete Riemannian metrics of nonnegative sectional curvature on certain open spin manifolds has nontrivial homotopy groups in infinitely many degrees. A new ingredient of independent interest is homotopy density of the subspace of metrics with c…

2018-05-06abs ↗pdf ↗

Study on free boundary minimal hypersurfaces in Schwarzschild space, proving zero Morse index for certain hypersurfaces.

problem Analyzing free boundary minimal hypersurfaces in the Riemannian Schwarzschild space.
method Variational methods and geometric analysis.
result Zero Morse index for certain free boundary rotationally symmetric totally geodesic hypersurfaces in the Riemannian Schwarzschild space.

In terms of the stock exchange returns, we compute the analytic expression of the probability distributions F{DAX,+} and F{DAX,-} of the normalized positive and negative DAX (Germany) index daily returns r(t). Furthermore, we define the alpha re-scaled DAX daily index positive returns r(t)^alpha and negative returns (-…

2010-04-07abs ↗pdf ↗

We study a class of localized indices for the Dirac type operators on a complete Riemannian orbifold, where a discrete group acts properly, co-compactly and isometrically. These localized indices, generalizing the L2L^2-index of Atiyah, are obtained by taking certain traces of the higher index for the Dirac type operat…

2013-07-08abs ↗pdf ↗

We give a framework of localization for the index of a Dirac-type operator on an open manifold. Suppose the open manifold has a compact subset whose complement is covered by a family of finitely many open subsets, each of which has a structure of the total space of a torus bundle. Under an acyclic condition we define t…

2009-10-02abs ↗pdf ↗

Single index model is a powerful yet simple model, widely used in statistics, machine learning, and other scientific fields. It models the regression function as g(<a,x>)g(<a,x>), where a is an unknown index vector and x are the features. This paper deals with a nonlinear generalization of this framework to allow for a regre…

2019-02-24abs ↗pdf ↗

Paper tackles privacy-preserving data density issues using deconvolution.

problem Privacy-preserving noise affects data density, leading to under/over-estimation.
method Develops deconvoluting kernel density estimators and regression models.
result Demonstrates improved accuracy in estimating heavy-hitters with locally differential data.

The paper localizes an index and provides a condition for the orientability of a monopole moduli space.

problem Localization of a KO(extpt)KO^{\ast}( ext{pt})-valued index and orientability of the Pin(2)Pin^-(2) monopole moduli space.
method Introducing G±(n,s+,s)G^{\pm}(n,s^+,s^-) structures and formulating characteristic submanifolds for these structures.
result The KO(pt)KO^*(pt)-valued index is localized to the characteristic submanifold, and a condition for the moduli space to be orientable is provided.

Study measures inequality in social-economic systems using Fokker-Planck equations and Lotka-Volterra dynamics.

problem Measuring inequality in oscillatory social-economic systems described by Fokker-Planck equations and Lotka-Volterra dynamics.
method Used Fokker-Planck equations and Lotka-Volterra dynamics to model inequality, focusing on coefficient of variation as a measure.
result Inequality initially tends to decrease in oscillatory systems, contrary to steady-state models.

Local constancy of index for certain gradient mappings proved.

problem Proving the local constancy of the index for specific gradient mappings.
method Using a more general theorem for quasiregular gradient mappings, deducing the result from the Hessian's properties.
result The index is locally constant for C1,1C^{1,1} functions with uniformly positive determinant Hessian almost everywhere.

We generalize Roe's index theorem for graded generalized Dirac operators on amenable manifolds to multigraded elliptic uniform pseudodifferential operators. The generalization will follow from a local index theorem that is valid on any manifold of bounded geometry. This local formula incorporates the uniform estimates …

2018-06-06abs ↗pdf ↗

Non-parametric estimation of a multivariate density estimation is tackled via a method which combines traditional local smoothing with a form of global smoothing but without imposing a rigid structure. Simulation work delivers encouraging indications on the effectiveness of the method. An application to density-based c…

2016-10-07abs ↗pdf ↗

We study the temporal evolution of the market efficiency in the stock markets using the complexity, entropy density, standard deviation, autocorrelation function, and probability distribution of the log return for Standard and Poor's 500 (S&P 500), Nikkei stock average index, and Korean composition stock price index (K…

2007-01-16abs ↗pdf ↗