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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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4896144192 · Jun 202019922001200920172026
48 results for second-order cone constraints

This paper mainly aims to establish the well-posedness on time interval [0,ε12T][0,\varepsilon^{-\frac{1}{2}}T] of the classical initial problem for the bosonic membrane in the light cone gauge. Here ε\varepsilon is the small parameter measures the nonlinear effects. In geometric, the bosonic membrane are timelike submanifo…

2013-06-09abs ↗pdf ↗

The Einstein equations in wave map gauge are a geometric second order system for a Lorentzian metric. To study existence of solutions of this hyperbolic quasi diagonal system with initial data on a characteristic cone which are not zero in a neighbourhood of the vertex one can appeal to theorems due to Cagnac and Dossa…

2010-12-02abs ↗pdf ↗

Paper derives estimates for complex Hessian equations on Hermitian manifolds.

problem Estimating solutions to complex Hessian equations on Hermitian manifolds.
method Derives second order estimates for solutions in a specific cone.
result Establishes second order estimates for solutions in Γk+1Γ_{k+1} cone.

Robust MCVaR portfolio optimization using RKHS for risk management.

problem Minimizing portfolio risk while achieving higher returns under uncertainty.
method Introduces a robust MCVaR model with ellipsoidal support and RKHS uncertainty set for chance constraint.
result Robust model outperforms nominal and market portfolios in various market conditions.

The SCMU algorithm computes cone factorizations for symmetric cones, improving upon existing methods.

problem Computing cone factorizations for symmetric cones in optimization.
method Introduces and analyzes the symmetric-cone multiplicative update (SCMU) algorithm.
result The SCMU algorithm non-decreases the squared loss objective.

Improved Compressed Sensing by optimizing sparse solutions with mixed integer programming.

problem Finding sparse solutions to linear measurements with numerical tolerance.
method Introducing an 2\ell_2 regularized formulation, reformulating as a mixed integer second order cone program, deriving a second order cone relaxation, and developing a custom branch-and-bound algorithm.
result Our approach produces solutions that are on average 6.22% more sparse compared to state-of-the-art methods.

The paper explores solving inverse problems for ODEs with and without constraints.

problem Understanding when second order ODEs can represent Lagrangian models with or without constraints.
method Geometric techniques to address the inverse problem for both constrained and unconstrained systems of second order ODEs.
result The constrained case presents more ambiguities and complexities than the unconstrained one.

The paper tackles online resource allocation with uncertain coefficients and chance constraints.

problem Online stochastic resource allocation problem with chance constraints.
method Linearization and primal-dual algorithms with heuristic corrections.
result Optimality gap and constraint violation are on the order of √n.

Paper introduces second-order Esscher densities for continuous-time models.

problem Modeling continuous-time market models with second-order Esscher densities.
method Introduced linear and exponential classes of second-order Esscher densities, characterized using semimartingale characteristics and pointwise equations.
result Characterized the relationship between linear and exponential classes for one-dimensional case and showed their connection in compound Poisson and jump-diffusion models.

Solves second-order PDEs using quotients and differential invariants.

problem Solving second-order PDEs with first-order quotients.
method Solve the quotient PDE using differential invariants, then add new constraints to solve the original PDE.
result New method for solving second-order scalar PDEs with infinite-dimensional symmetry algebras.

New inequality criterion for a mean field equation on spheres.

problem Finding uniqueness in a mean field equation on spheres.
method Established a new Moser-Trudinger-Onofri inequality with a constraint on moments deviation.
result A threshold for deviation is a uniqueness criterion for the mean field equation.

New method solves stochastic optimization problems with random models.

problem Optimizing stochastic objectives with deterministic constraints.
method Trust-Region Sequential Quadratic Programming with random model.
result Global convergence guarantees for first- and second-order stationary points.

This paper proves a rigidity result for annuli in RCD(K,N)RCD(K, N)-spaces.

problem The rigidity of annuli in RCD(K,N)RCD(K, N)-spaces.
method The approach uses second order differentiation and a method similar to Cheeger-Colding's.
result Annuli in RCD(K,N)RCD(K, N)-spaces with certain curvature conditions are measured Gromov-Hausdorff close to a warped product.

SOC-ICNN expands neural network representational capacity by using conic optimization.

problem Restrictive representational capacity of ReLU-based ICNNs.
method Proposes SOC-ICNN architecture that uses Second-Order Cone Programming.
result SOC-ICNN strictly expands representational space without increasing complexity.

The paper classifies periodic solitons in curve flows on the light-cone.

problem Investigating periodic solitons in curve flows on the light-cone.
method Deriving Harnack inequality for heat flow, classifying space-periodic solitons for a third-order curvature flow.
result Closed soliton solutions form a family of transcendental curves with specific rotation indices.

Solves Merton's investment-consumption problem with certainty equivalent approach.

problem Maximizing CRRA utility of consumption over time and investment mix.
method Identifies a certainty equivalent problem for the Merton problem, reformulates it as an SOCP, and applies it to model predictive control.
result The certainty equivalent problem can be solved as an SOCP, facilitating model predictive control.

Paper proposes a method to find approximate SOSP for nonconvex conic optimization problems.

problem Finding approximate second-order stationary points in nonconvex conic optimization.
method Newton-CG based barrier method with complexity guarantees.
result Achieves iteration complexity of O(ε^(-3/2)) for finding (ε,√ε)-SOSP.

Enhanced indexation with sector constraints using SSD for better portfolio performance.

problem Constructing a portfolio that outperforms a market index while respecting sector investment proportions.
method Subset second-order stochastic dominance (subset SSD) applied to asset subset constraints.
result Subset SSD approach outperforms S&P500 and standard SSD approaches.

We prove that Wilson loop expectation values for arbitrary simple closed contours obey an area law up to second order in perturbative two-dimensional Yang-Mills theory. Our analysis occurs within a general family of axial-like gauges, which include and interpolate between holomorphic gauge and the Wu-Mandelstam-Liebran…

2016-01-18abs ↗pdf ↗

Nearly Kähler manifolds are the Riemannian 6-manifolds admitting real Killing spinors. Equivalently, the Riemannian cone over a nearly Kähler manifold has holonomy contained in G2. In this paper we study the deformation theory of nearly Kähler manifolds, showing that it is obstructed in general. More precisely, we show…

2016-01-18abs ↗pdf ↗

We study the problem of removable singularities for degenerate elliptic equations. Let F be a fully nonlinear second-order partial differential subequation of degenerate elliptic type on a manifold X. We study the question: Which closed subsets E in X have the property that every F-subharmonic function (subsolution) on…

2013-03-02abs ↗pdf ↗

The jet bundle description of time-dependent mechanics is revisited. The constraint algorithm for singular Lagrangians is discussed and an exhaustive description of the constraint functions is given. By means of auxiliary connections we give a basis of constraint functions in the Lagrangian and Hamiltonian sides. An ad…

2001-05-10abs ↗pdf ↗

We consider the problem of decomposing a multivariate polynomial as the difference of two convex polynomials. We introduce algebraic techniques which reduce this task to linear, second order cone, and semidefinite programming. This allows us to optimize over subsets of valid difference of convex decompositions (dcds) a…

2015-10-06abs ↗pdf ↗

We briefly review the notion of second order constrained (continuous) system (SOCS) and then propose a discrete time counterpart of it, which we naturally call discrete second order constrained system (DSOCS). To illustrate and test numerically our model, we construct certain integrators that simulate the evolution of …

2013-12-06abs ↗pdf ↗

New conic quadratic formulations improve outlier detection in regression models.

problem Detecting outliers in regression models with corrupted data.
method Deriving stronger second-order conic relaxations without big-M constraints.
result Proposed formulations are significantly faster than existing methods.

The entropy-degree theorem applies to Alexandrov spaces with curvature constraints.

problem Geometric obstructions and volume bounds in singular spaces.
method Developed new degree theorem for Alexandrov spaces using integral currents.
result Entropy-volume minimization prevents metric singularities in Gromov-Hausdorff limits.

We show that, for generative classifiers, conditional independence corresponds to linear constraints for the induced discrimination functions. Discrimination functions of undirected Markov network classifiers can thus be characterized by sets of linear constraints. These constraints are represented by a second order fi…

2018-11-12abs ↗pdf ↗

We prove some old and new isoperimetric inequalities with the best constant using the ABP method applied to an appropriate linear Neumann problem. More precisely, we obtain a new family of sharp isoperimetric inequalities with weights (also called densities) in open convex cones of Rn\mathbb{R}^n. Our result applies to…

2013-04-05abs ↗pdf ↗