We study the problem of existence of regions separating a given amount of volume with the least possible perimeter inside a Euclidean cone. Our main result shows that nonexistence for a given volume implies that the isoperimetric profile of the cone coincides with the one of the half-space. This allows us to give some …
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.
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Unified framework for hard affine SDP constraints in vRKHSs.
Compact hypersurfaces minimize area in convex cones with free boundary.
This paper mainly aims to establish the well-posedness on time interval of the classical initial problem for the bosonic membrane in the light cone gauge. Here is the small parameter measures the nonlinear effects. In geometric, the bosonic membrane are timelike submanifo…
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…
Paper derives estimates for complex Hessian equations on Hermitian manifolds.
Robust MCVaR portfolio optimization using RKHS for risk management.
New method learns BN structures from data efficiently.
We consider a smooth Euclidean solid cone endowed with a smooth homogeneous density function used to weight Euclidean volume and hypersurface area. By assuming convexity of the cone and a curvature-dimension condition we prove that the unique compact, orientable, second order minima of the weighted area under variation…
Associative submanifolds in nearly parallel -manifolds are minimal 3-submanifolds in spin 7-manifolds with a real Killing spinor. The Riemannian cone over has the holonomy group contained in and the Riemannian cone over is a Cayley submanifold. Infinitesimal deformations of associat…
The SCMU algorithm computes cone factorizations for symmetric cones, improving upon existing methods.
Improved Compressed Sensing by optimizing sparse solutions with mixed integer programming.
We study a cutting-plane method for semidefinite optimization problems (SDOs), and supply a proof of the method's convergence, under a boundedness assumption. By relating the method's rate of convergence to an initial outer approximation's diameter, we argue that the method performs well when initialized with a second-…
This paper proposes an Adaptive Stochastic Model Predictive Control (MPC) strategy for stable linear time-invariant systems in the presence of bounded disturbances. We consider multi-input, multi-output systems that can be expressed by a Finite Impulse Response (FIR) model. The parameters of the FIR model corresponding…
The paper explores solving inverse problems for ODEs with and without constraints.
Optimization with inequality constraints using embedded gradient vector field method
Paper tackles hard shape constraints in kernel machines.
The paper tackles online resource allocation with uncertain coefficients and chance constraints.
New method for linear connections in ODEs with constraints.
New algorithm for online optimization over symmetric cones, unifying previous methods.
Paper introduces second-order Esscher densities for continuous-time models.
A parameter-invariant variational problem with a manifestly covariant Lagrangian function of second order is considered, which covers the case of the free relativistic top at constraint manifold of constant acceleration
Solves second-order PDEs using quotients and differential invariants.
New inequality criterion for a mean field equation on spheres.
We consider continuous-time mean-variance portfolio selection with bankruptcy prohibition under convex cone portfolio constraints. This is a long-standing and difficult problem not only because of its theoretical significance, but also for its practical importance. First of all, we transform the above problem into an e…
New method solves stochastic optimization problems with random models.
We propose a unified framework to address a family of classical mixed-integer optimization problems with logically constrained decision variables, including network design, facility location, unit commitment, sparse portfolio selection, binary quadratic optimization, sparse principal analysis and sparse learning proble…
Given a geodesic inside a simply-connected, complete, non-positively curved Riemannian (NPCR) manifold M, we get an associated geodesic inside the asymptotic cone Cone(M). Under mild hypotheses, we show that if the latter is contained inside a bi-Lipschitz flat, then the original geodesic supports a non-trivial, orthog…
This paper proves a rigidity result for annuli in -spaces.
SOC-ICNN expands neural network representational capacity by using conic optimization.
The paper classifies periodic solitons in curve flows on the light-cone.
Solves Merton's investment-consumption problem with certainty equivalent approach.
Paper proposes a method to find approximate SOSP for nonconvex conic optimization problems.
Enhanced indexation with sector constraints using SSD for better portfolio performance.
In this paper we study a class of physical systems that combine a finite number of mechanical and thermodynamic observables. We call them finite dimensional thermo-mechanical systems. We introduce these systems by means of simple examples. The evolution equations of the involved observables are obtained in each example…
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…
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…
We study the Hamiltonian formalisms of the second order degenerate Clèment and Sarıoğlu-Tekin Lagrangians. The Dirac-Bergmann constraint algorithm is employed while arriving at the total Hamiltonian functions and the Hamilton's equations on the associated momemtum phase spaces whereas the Gotay-Nester-Hinds algorithm i…
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…
New proof of Sobolev inequality with constraints on sphere.
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…
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…
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 …
New conic quadratic formulations improve outlier detection in regression models.
New method solves sparse PCA for multiple components efficiently.
The entropy-degree theorem applies to Alexandrov spaces with curvature constraints.
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…
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 . Our result applies to…