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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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57114170227 · Jun 202019922001200920172026
48 results for Squared families

Squared families are a new model class derived from linear transformations, offering convenient properties and universal approximation.

problem Developing a new class of probability models that are easier to handle and have useful properties.
method Introducing squared families as families of probability densities obtained by squaring a linear transformation of a statistic, and showing their properties and applications.
result Squared families have convenient properties and can approximate target densities well.

Exponential family extensions of principal component analysis (EPCA) have received a considerable amount of attention in recent years, demonstrating the growing need for basic modeling tools that do not assume the squared loss or Gaussian distribution. We extend the EPCA model toolbox by presenting the first exponentia…

2012-03-15abs ↗pdf ↗

We consider adaptive system identification problems with convex constraints and propose a family of regularized Least-Mean-Square (LMS) algorithms. We show that with a properly selected regularization parameter the regularized LMS provably dominates its conventional counterpart in terms of mean square deviations. We es…

2010-12-22abs ↗pdf ↗

The study finds arithmetic groups often in square-tiled surface monodromies.

problem Understanding arithmetic properties of square-tiled surfaces.
method Analyzing variations of Hodge structures and Kontsevich-Zorich monodromies.
result Arithmetic groups are frequent in low genus square-tiled surfaces.

The square-peg problem is solved using configuration spaces and multijet transversality.

problem Proving that every simple closed curve in the plane has an odd number of inscribed squares.
method Using the multijet transversality theorem and configuration spaces, we find a dense set of smooth embeddings for which the configuration space of points is transverse to any submanifold.
result A dense family of smoothly embedded circles in the plane and in Rn\mathbb{R}^n have an odd number of inscribed square-like quadrilaterals.

The family of temporal difference (TD) methods span a spectrum from computationally frugal linear methods like TD(λ) to data efficient least squares methods. Least square methods make the best use of available data directly computing the TD solution and thus do not require tuning a typically highly sensitive learning r…

2016-11-28abs ↗pdf ↗

This paper reviews SDR methods for multivariate response regression.

problem Handling sufficient dimension reduction for multivariate response regression.
method Characterizes SDR estimators as inverse or forward regression methods.
result Pooled marginal, projective resampling, distance-based, ordinary least squares, partial least squares, and semiparametric SDR estimators are discussed.

We prove a transversality "lifting property" for compactified configuration spaces as an application of the multijet transversality theorem: the submanifold of configurations of points on an arbitrary submanifold of Euclidean space may be made transverse to any submanifold of the configuration space of points in Euclid…

2014-02-25abs ↗pdf ↗

New groups derived from square configurations have right-angled and HNN structures.

problem Understanding the fundamental groups of square configurations and their homotopy properties.
method Analyzing configuration spaces and their fundamental groups, proving group presentations and homotopy equivalences.
result The fundamental groups of certain square configurations have minimal presentations with commutator relators and are HNN extensions of specific meta-square groups.

For every spatial embedding of each graph in the Petersen family, it is known that the sum of the linking numbers over all of the constituent 2-component links is congruent to 1 modulo 2. In this paper, we give an integral lift of this formula in terms of the square of the linking number and the second coefficient of t…

2012-09-10abs ↗pdf ↗

Origami graphs' Euler characteristics grow as origami complexity increases.

problem Proving McMullen's conjecture about origami graphs' expansion properties.
method Counting integral and orbifold points on algebraic hypersurfaces, Teichmüller curves, and pseudo-Anosov diffeomorphisms.
result The absolute values of Euler characteristics go to infinity with origami complexity.

The paper is on the vanishing topology of singular Milnor fibres of holomorphic families of arbitrary square, symmetric and skew-symmetric matrices with sufficiently many parameters. We define vanishing cycles on such fibres, prove an extended form of the Damon-Pike μ=τμ=τ conjecture about the families of a special type…

2019-09-10abs ↗pdf ↗

SNEPPPs use squared neural networks to efficiently model Poisson point processes.

problem Efficiently modeling Poisson point processes with flexibility.
method Parameterizing intensity function with squared norm of a two-layer neural network.
result Closed-form integration of intensity function for quadratic time computation.

The eigenvalue problem for the square integrable solutions is studied usually for elliptic equations. In this note we consider such a problem for the hyperbolic Klein-Gordon equation on Lorentzian manifolds. The investigation could help to answer the question why elementary particles have a discrete mass spectrum. An i…

2006-03-28abs ↗pdf ↗

This paper focuses on the graphs in the Petersen family, the set of minor minimal intrinsically linked graphs. We prove there is a relationship between algebraic linking of an embedding and knotting in an embedding. We also present a more explicit relationship for the graph K3,3,1K_{3,3,1} between knotting and linking, whi…

2010-08-02abs ↗pdf ↗

We study cubical sets without degeneracies, which we call square sets. These sets arise naturally in a number of settings and they have a beautiful intrinsic geometry; in particular a square set C has an infinite family of associated square sets J^i(C), i=1,2,..., which we call James complexes. There are mock bundle pr…

2003-01-30abs ↗pdf ↗

Let SS be an nn-punctured sphere, with n3n \geq 3. We prove that (n3)\binom{n}{3} is the maximum size of a family of pairwise non-homotopic simple arcs on SS joining a fixed pair of distinct punctures of SS and pairwise intersecting at most twice. On the way, we show that a square annular diagram AA has a corner on …

2019-06-14abs ↗pdf ↗

Earlier work with Robert Gompf and Abigail Thompson classified, via a natural slope indexed by the rationals, all two-component links which contain the square knot and from which (S1×S2)#(S1×S2)(S^1 \times S^2) \# (S^1 \times S^2) can be obtained by surgery. It was argued that a certain family LnL_n of such links probably contradic…

2012-08-06abs ↗pdf ↗

We have shown that the Beltrami Theorem in Riemannian geometry is still true for square metrics if the dimension n3n\ge 3, namely, an n(3)n(\ge 3)-dimensional square metric is locally projectively flat if and only if it is of scalar flag curvature. In this paper, we go on with the study of the Beltrami Theorem for a larg…

2013-02-14abs ↗pdf ↗

This paper calculates the derivative of surface holonomy for non-abelian gerbes.

problem Calculating the derivative of surface holonomy for non-abelian gerbes.
method Explicit calculation of the derivative formula for surface holonomy of squares mapped into the base manifold.
result Derivation of a formula for the derivative of surface holonomy of squares mapped into the base manifold.

Unified multi-view learning framework using OPLS with regularization and deep extensions.

problem Improving multi-view learning for classification and feature extraction.
method Orthonormalized Partial Least Squares (OPLS) with regularization and deep extensions.
result Unified multi-view learning framework with improved performance.

Using Gauge theoretical techniques employed by Lisca for 2-bridge knots and by Greene-Jabuka for 3-stranded pretzel knots, we show that no member of the family of Montesinos knots M(0;[m_1+1,n_1+2],[m_2+1,n_2+2],q), with certain restrictions on m_i, n_i, and q, can be (smoothly) slice. Our techniques use Donaldson's di…

2008-09-07abs ↗pdf ↗

Unified analysis of reweighted least-squares algorithms for linear models.

problem Recovering unknown signals from linear measurements using reweighted least squares.
method Unified asymptotic analysis of IRLS, lin-RFM, and alternating minimization algorithms.
result The algorithms can achieve favorable performance in a few iterations with appropriate reweighting.

New CH covariance class improves spatial statistics by balancing differentiability and tail behavior.

problem Lack of control over mean-square differentiability and tail behavior in Matérn covariance functions.
method Developed a new Confluent Hypergeometric (CH) covariance class using a scale mixture of Matérn and polynomial covariances.
result The CH class offers improved theoretical properties and better performance in extrapolative settings.

Explicitly constructed 3XOR instances hard for Sum-of-Squares hierarchy.

problem Hard instances for Sum-of-Squares hierarchy.
method Based on high-dimensional expanders (LSV complexes), using cosystolic expansion and local isoperimetric inequality.
result Constructs explicit 3XOR instances hard for O(logn)O(\sqrt{\log n}) levels of Sum-of-Squares hierarchy.

Eisenbud Popescu and Walter have constructed certain special 4-dimensional sextic hypersurfaces as Lagrangian degeneracy loci. We prove that the natural double cover of a generic EPW-sextic is a deformation of the Hilbert square of a K3-surface and that the family of such varieties is locally complete for deformations …

2005-07-19abs ↗pdf ↗

Unified CCA methods for large-scale data with fast SGD algorithms.

problem Computational infeasibility of classical CCA methods for large-scale data.
method Unconstrained objective, stochastic gradient descent (SGD) algorithms.
result Significantly faster convergence and higher correlations than previous methods.

Dual-sPLS improves feature selection and prediction in high-dimensional data.

problem Relating variables to a response in high-dimensional chemometric problems.
method Generalizes PLS1 algorithm with dual norm penalizations and a shrinking ratio parameter.
result Favorably compares to similar regression methods on simulated and real chemical data.

This paper establishes a statistical versus computational trade-off for solving a basic high-dimensional machine learning problem via a basic convex relaxation method. Specifically, we consider the {\em Sparse Principal Component Analysis} (Sparse PCA) problem, and the family of {\em Sum-of-Squares} (SoS, aka Lasserre/…

2015-07-23abs ↗pdf ↗

This paper presents a general framework for norm-based capacity control for Lp,qL_{p,q} weight normalized deep neural networks. We establish the upper bound on the Rademacher complexities of this family. With an Lp,qL_{p,q} normalization where qpq\le p^*, and 1/p+1/p=11/p+1/p^{*}=1, we discuss properties of a width-independent ca…

2018-10-03abs ↗pdf ↗