Results 51 to 60 of about 6,730 (164)
Robust multitask feature learning with adaptive Huber regressions
Abstract When data from multiple tasks have outlier contamination, existing multitask learning methods perform less efficiently. To address this issue, we propose a robust multitask feature learning method by combining the adaptive Huber regression tasks with mixed regularization. The robustification parameters can be chosen to adapt to the sample size,
Yuan Zhong, Xin Gao, Wei Xu
wiley +1 more source
We prove that every function $f:\mathbb{R}^n\to \mathbb{R}$ satisfies that the image of the set of critical points at which the function $f$ has Taylor expansions of order $n-1$ and non-empty subdifferentials of order $n$ is a Lebesgue-null set.
Azagra, Daniel +2 more
core +1 more source
Learning in random utility models via online decision problems
Abstract This paper examines the Random Utility Model (RUM) in repeated stochastic choice settings where decision‐makers lack full information about payoffs. We propose a gradient‐based learning algorithm that embeds RUM into an online decision‐making framework.
Emerson Melo
wiley +1 more source
In Part 1 of this paper, we have estimated the Fr\'echet coderivative and the Mordukhovich coderivative of the stationary point set map of a smooth parametric optimization problem with one smooth functional constraint under total perturbations.
Huyen, Duong Thi Kim +2 more
core +1 more source
Conformal optimization of eigenvalues on surfaces with symmetries
Abstract Given a conformal action of a discrete group on a Riemann surface, we study the maximization of Laplace and Steklov eigenvalues within a conformal class, considering metrics invariant under the group action. We establish natural conditions for the existence and regularity of maximizers. Our method simplifies the previously known techniques for
Denis Vinokurov
wiley +1 more source
Subdifferential calculus for a quasiconvex function with generator
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Suzuki, Satoshi, Kuroiwa, Daishi
openaire +1 more source
Superlinear perturbations of a double‐phase eigenvalue problem
Abstract We consider a perturbed version of an eigenvalue problem for the double‐phase operator. The perturbation is superlinear, but need not satisfy the Ambrosetti–Robinowitz condition. Working on the Sobolev–Orlicz space W01,η(Ω)$ W^{1,\eta }_{0}(\Omega)$ with η(z,t)=α(z)tp+tq$ \eta (z,t)=\alpha (z)t^{p}+t^{q}$ for 1
Yunru Bai +2 more
wiley +1 more source
ABSTRACT Although finite elements were made available for FFT‐based computational homogenization methods, they are seldomly used for inelastic computations because traditionally the constitutive law is evaluated at each quadrature point of the element, making the storage of that many internal variables necessary, as well.
Flavia Gehrig, Matti Schneider
wiley +1 more source
Global attractors for gradient flows in metric spaces [PDF]
We develop the long-time analysis for gradient flow equations in metric spaces. In particular, we consider two notions of solutions for metric gradient flows, namely energy and generalized solutions.
Rossi, Riccarda +2 more
core
Optimal Control of AB Caputo Fractional Stochastic Integrodifferential Control System with Noninstantaneous Impulses. ABSTRACT This study is concerned with the existence of mild solution and optimal control for the Atangana–Baleanu fractional stochastic integrodifferential system with noninstantaneous impulses in Hilbert spaces. We verify the existence
Murugesan Johnson +2 more
wiley +1 more source

