Research
On-device research index

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.

168,694 papers · 148 categories

Trend · papers per month

4794140187 · May 202619922001200920172026
48 results for Separability Index

DSI measures dataset separability for neural networks.

problem Difficulty in separating different classes of data in neural networks.
method Created the Distance-based Separability Index (DSI) to quantify dataset separability.
result DSI effectively measures dataset separability and indicates similar distributions of different classes.

In 1987, Kalai proved that stacked spheres of dimension d3d\geq 3 are characterised by the fact that they attain equality in Barnette's celebrated Lower Bound Theorem. This result does not extend to dimension d=2d=2. In this article, we give a characterisation of stacked 22-spheres using what we call the {\em separatio…

2014-03-24abs ↗pdf ↗

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.

If F is a surface with boundary, then a finitely generated subgroup without peripheral elements of G = π_1(F) can be separated from finitely many other elements of G by a finite index subgroup of G corresponding to a finite cover F' with the same number of boundary components as F .

2012-04-20abs ↗pdf ↗

Let f be a smooth Morse function on an infinite dimensional separable Hilbert manifold, all of whose critical points have infinite Morse index and co-index. For any critical point x choose an integer a(x) arbitrarily. Then there exists a Riemannian structure on M such that the corresponding gradient flow of f has the f…

2004-03-31abs ↗pdf ↗

Membership in the Russell 1000 and 2000 Indices is based on a ranking of market capitalization in May. Each index is separately value weighted such that firms just inside the Russell 2000 are comparable in size to firms just outside (i.e. at the bottom of the Russell 1000) but have much higher index weights. These feat…

2015-09-01abs ↗pdf ↗

We give a new, effective proof of the separability of cubically convex-cocompact subgroups of special groups. As a consequence, we show that if GG is a virtually compact special hyperbolic group, and QGQ\leq G is a KK-quasiconvex subgroup, then any gGQg\in G-Q of word-length at most nn is separated from QQ by a subg…

2015-01-28abs ↗pdf ↗

The paper challenges the validity of cluster validity measures in unsupervised learning.

problem The validity of cluster validity measures in selecting optimal clusterings.
method The authors investigate the use of cluster validity measures as objective functions in unsupervised learning and introduce a new variant of the Dunn index.
result Many cluster validity measures promote clusterings that do not match expert knowledge well.

We show that for all but finitely many compact orientable surfaces, any superinjective map from the complex of separating curves into the Torelli complex is induced by an element of the extended mapping class group. As an application, we prove that any injective homomorphism from a finite index subgroup of the Johnson …

2009-11-19abs ↗pdf ↗

Study introduces a new Allen-Cahn energy on hypersurfaces and analyzes its properties.

problem Analyzing geometric variations of the Allen-Cahn energy on hypersurfaces.
method Establishes Γ-convergence, computes variations, and analyzes the linearized equation.
result Shows that the index and nullity of the energy are related to the Allen-Cahn index and nullity.

For a knot KS3K\subset S^3, its exterior E(K)=S3\η(K)E(K) = S^3\backslashη(K) has a singular foliation by Seifert surfaces of KK derived from a circle-valued Morse function f ⁣:E(K)S1f\colon E(K)\to S^1. When ff is self-indexing and has no critical points of index 0 or 3, the regular levels that separate the index-1 and index-2 critica…

2018-12-17abs ↗pdf ↗

Paper introduces PHI to identify structurally distinct payment patterns in UK municipal procurement.

problem Vulnerability of public procurement to error, fraud, and corruption in high-volume transactions.
method Introduces Payment Heterogeneity Index (PHI) using Gaussian Mixture Model (GMM) and non-parametric statistics.
result Identifies a significant cohort with structurally distinct payment patterns, improving procurement oversight.

A celebrated theorem of Marshall Hall Jr. implies that finitely generated free groups are subgroup separable and that all of their finitely generated subgroups are retracts of finite-index subgroups. We use topological techniques inspired by the work of Stallings to prove that all limit groups share these two propertie…

2006-05-19abs ↗pdf ↗

Randomly biased data makes complex models as easy to learn as simple ones.

problem Learning complex models like multi-index and sparse Boolean functions.
method Introducing a small random shift in the first moment of the data distribution.
result Randomly biased data makes Gaussian single index models and sparse Boolean functions as easy to learn as linear functions.

Noise Sensitivity Exponent controls statistical-computational gaps in learning.

problem Understanding when learning is statistically possible yet computationally hard in high-dimensional statistics.
method Investigating statistical-computational gaps in single- and multi-index models using Noise Sensitivity Exponent.
result Noise Sensitivity Exponent governs statistical-computational gaps in high-dimensional learning.

Graphs can model interactions between vertices, but how well depends on graph structure.

problem Lack of formal characterization of GNNs' ability to model interactions between vertices.
method Formalized interaction strength using separation rank and quantified it for different partitions of vertices.
result GNNs' ability to model interactions is primarily determined by the partition's walk index.

Nonnegative matrix factorization (NMF) is a linear dimensionality technique for nonnegative data with applications such as image analysis, text mining, audio source separation and hyperspectral unmixing. Given a data matrix MM and a factorization rank rr, NMF looks for a nonnegative matrix WW with rr columns and a …

2019-05-30abs ↗pdf ↗

A deep neural network detects sleep events in polysomnograms with high accuracy.

problem Manual scoring of sleep events in clinical analysis is inconsistent and time-consuming.
method A single deep neural network architecture trained on 1653 recordings for joint detection of arousals, leg movements, and sleep disordered breathing.
result Joint detection of sleep events yields higher accuracy compared to separate models, and correlates well with manual annotations.

We associate cube complexes called completions to each subgroup of a right-angled Coxeter group (RACG). A completion characterizes many properties of the subgroup such as whether it is quasiconvex, normal, finite-index or torsion-free. We use completions to show that reflection subgroups are quasiconvex, as are one-end…

2019-08-23abs ↗pdf ↗

Query access significantly speeds up learning Multi-Index Models under Gaussian distribution.

problem Agnostically learning Multi-Index Models (MIMs) under Gaussian distribution.
method Query access for MIMs with complexity O(k)poly(1/ε)  poly(d)O(k)^{\mathrm{poly}(1/ε)} \; \mathrm{poly}(d) under standard regularity assumptions.
result Query access gives significant runtime improvements over random examples for agnostically learning MIMs.

For all but finitely many compact orientable surfaces, we show that any superinjective map from the complex of separating curves into itself is induced by an element of the extended mapping class group. We apply this result to proving that any finite index subgroup of the Johnson kernel is co-Hopfian. Analogous propert…

2009-11-20abs ↗pdf ↗

Physics-Informed Neural Network (PINN) computes the Morse index of the critical catenoid.

problem Computing the Morse index of the critical catenoid
method Physics-Informed Neural Network (PINN) enforces parity and eigenvalue as trainable parameters
result Returns eigenvalues within 10610^{-6} to 10410^{-4} of exact values

We find the wealth distribution for an economic agent in the financial market, in analogy with standard derivation of generaliz Boltzman (Tsallis) factor in statistical mechanics. In this respect, Tsallis entropic index separates two different regimes, the large and small size market. The Pareto like wealth distributio…

2004-04-28abs ↗pdf ↗

The paper shows how solutions of perturbed Dirac operators concentrate near singular sets.

problem Understanding concentration of solutions for perturbed Dirac operators.
method Analyzing the algebraic criterion on $(c, \A)$ and spectral properties of deformed Laplacians.
result Proves an index localization theorem based on spectral separation properties.

We investigate the waiting-time distribution of the absolute return in the Korean stock-market index KOSPI. We define the waiting time as a time interval during which the normalized absolute return remains continuously below a threshold rcr_c. Through an exponential bin plot, we observe that the waiting-time distributi…

2005-08-30abs ↗pdf ↗

Let K be the subgroup of the extended mapping class group, Mod(S), generated by Dehn twists about separating curves. Assuming that S is a closed, orientable surface of genus at least 4, we confirm a conjecture of Farb that Comm(K), Aut(K) and Mod(S) are all isomorphic. More generally, we show that any injection of a fi…

2004-04-25abs ↗pdf ↗

Post-estimation smoothing improves prediction accuracy with structural indices.

problem Using natural structural indices in machine learning without losing robustness.
method A post-estimation smoothing operator that separates from the original predictor.
result Post-estimation smoothing improves accuracy over original predictors under simple conditions.

We present proofs of basic results, including those developed by Harold Bell, for the plane fixed point problem: does every map of a non-separating plane continuum have a fixed point? Some of these results had been announced much earlier by Bell but without accessible proofs. We define the concept of the variation of a…

2010-04-01abs ↗pdf ↗

Vanilla SGD learns SIM from anisotropic data without explicit covariance estimation.

problem Learning SIM from anisotropic Gaussian inputs.
method Vanilla Stochastic Gradient Descent (SGD) trained on SIM with anisotropic input.
result Vanilla SGD adapts to anisotropic data's covariance structure.

New index improves anomaly detection in correlated time series data.

problem Challenges in evaluating cluster quality for anomaly detection.
method Introduced Synchronized Anomaly Agreement Index (SAAI) to assess cluster quality.
result Maximizing SAAI improves anomaly detection accuracy by 0.23 compared to SSC and by 0.32 compared to X-Means.

Choose any oriented link type X and closed braid representatives X[+], X[-] of X, where X[-] has minimal braid index among all closed braid representatives of X. The main result of this paper is a `Markov theorem without stabilization'. It asserts that there is a complexity function and a finite set of `templates' such…

2003-10-18abs ↗pdf ↗