Abstract: Survey on quadratic Hessian equations, their properties, and open problems.
arXiv research
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Unique minimal surfaces near quadratic cones are identified.
We consider the problem of solving a large-scale Quadratically Constrained Quadratic Program. Such problems occur naturally in many scientific and web applications. Although there are efficient methods which tackle this problem, they are mostly not scalable. In this paper, we develop a method that transforms the quadra…
In the paper, we consider three quadratic optimization problems which are frequently applied in portfolio theory, i.e, the Markowitz mean-variance problem as well as the problems based on the mean-variance utility function and the quadratic utility.Conditions are derived under which the solutions of these three optimiz…
We consider a proximal operator given by a quadratic function subject to bound constraints and give an optimization algorithm using the alternating direction method of multipliers (ADMM). The algorithm is particularly efficient to solve a collection of proximal operators that share the same quadratic form, or if the qu…
Paper addresses quadratic feasibility problems and their sample complexity.
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Python package for projecting onto quadratic hypersurfaces.
Quadratic regression involves modeling the response as a (generalized) linear function of not only the features but also of quadratic terms . The inclusion of such higher-order "interaction terms" in regression often provides an easy way to increase accuracy in already-high-dimensional problem…
The paper solves a utility-based hedging problem with quadratic costs.
We describe all pseudo-Riemannian metrics on closed surfaces whose geodesic flows admit nontrivial integrals quadratic in momenta. As an application, we solve the Beltrami problem on closed surfaces and prove the nonexistence of quadratically-superintegrable metrics of nonconstant curvature on closed surfaces
This paper concerns a method of selecting a subset of features for a sequential logit model. Tanaka and Nakagawa (2014) proposed a mixed integer quadratic optimization formulation for solving the problem based on a quadratic approximation of the logistic loss function. However, since there is a significant gap between …
The paper studies optimal transport in linear quadratic systems and derives interpolation inequalities.
Market maker optimizes SPX and VIX spread using quadratic rough Heston model.
Paper develops methods for non-quadratic loss low-rank matrix recovery.
Deep learning solves high-dimensional quadratic hedging problems.
A new algorithm for solving constrained convex optimization problems efficiently.
Paper presents an ADMM-based approach to efficiently integrate quadratic programming layers into neural networks.
Paper classifies conic submanifolds in control systems.
Investment strategy optimization from discrete to continuous models.
We introduce O-systems (Definition \ref{DO}) of orthogonal transformations of , and establish correspondences both between equivalence classes of Clifford systems and that of O-systems, and between O-systems and orthogonal multiplications of the form $μ:{\Bbb R}^{n} \times {\Bbb R}^{m} \longrightarr…
RL solves discrete LQ control with Gaussian optimal policy.
To determine the Lie groups that admit a flat (eventually complete) left invariant semi-Riemannian metric is an open and difficult problem. The main aim of this paper is the study of the flatness of left invariant semi Riemannian metrics on quadratic Lie groups i.e. Lie groups endowed with a bi-invariant semi Riemannia…
New method solves constrained stochastic optimization problems efficiently.
QENDy learns quadratic dynamics from nonlinear systems data.
To estimate the conditional probability functions based on the direct problem setting, V-matrix based method was proposed. We construct V-matrix based constrained quadratic programming problems for which the inequality constraints are inconsistent. In particular, we would like to present that the constrained quadratic …
New conic quadratic formulations improve outlier detection in regression models.
New method trains Boltzmann machines without supervision.
The study examines portfolio optimization with quadratic transaction costs, complicating the optimization process.
Algorithm reduces regret in partially observable systems by learning dynamics and using optimistic control.
An explicit (-1)^n-quadratic form over Z[Z^{2n}] representing the surgery problem E_8 x T^{2n} is obtained, for use in the Bryant-Ferry-Mio-Weinberger construction of 2n-dimensional exotic homology manifolds.
This paper introduces a method to incorporate risk sensitivity in RL using quadratic variation penalties.
In this paper we study a continuous-time stochastic linear quadratic control problem arising from mathematical finance. We model the asset dynamics with random market coefficients and portfolio strategies with convex constraints. Following the convex duality approach, we show that the necessary and sufficient optimalit…
In this paper, we analyze a real-valued reflected backward stochastic differential equation (RBSDE) with an unbounded obstacle and an unbounded terminal condition when its generator has quadratic growth in the -variable. In particular, we obtain existence, comparison, and stability results, and consider the opti…
Extends quadratic loss for SVM and deep learning to improve pattern correlation.
In this paper, we study a class of quadratic Backward Stochastic Differential Equations (BSDEs) which arises naturally when studying the problem of utility maximization with portfolio constraints. We first establish existence and uniqueness results for such BSDEs and then, we give an application to the utility maximiza…
We provide explicit solutions of certain forward-backward stochastic differential equations (FBSDEs) with quadratic growth. These particular FBSDEs are associated with quadratic term structure models of interest rates and characterize the zero-coupon bond price. The results of this paper are naturally related to simila…
New geometric Joyce structures on moduli spaces of quadratic differentials.
Optimal contracts are found for agents with quadratic effort costs.
Method solves complex optimization problems with high probability bounds.
Solves generalized twisted rabbit problems for higher degree polynomials.
Improved SVRG for quadratic functions achieves better performance and running times.
Study optimal hedging for claims with random weights in discrete time.
We describe all pseudo-Riemannian metrics on closed surfaces whose geodesic flows admit nontrivial integrals quadratic in momenta. As an application, we solve the Beltrami problem on closed surfaces, prove the nonexistence of quadratically-superintegrable metrics of nonconstant curvature on closed surfaces, and prove t…
We consider the exploration-exploitation tradeoff in linear quadratic (LQ) control problems, where the state dynamics is linear and the cost function is quadratic in states and controls. We analyze the regret of Thompson sampling (TS) (a.k.a. posterior-sampling for reinforcement learning) in the frequentist setting, i.…
Note on the computational complexity of Gromov-Wasserstein distance.
We develop algorithms for the numerical computation of the quadratic hedging strategy in incomplete markets modeled by pure jump Markov process. Using the Hamilton-Jacobi-Bellman approach, the value function of the quadratic hedging problem can be related to a triangular system of parabolic partial integro-differential…