The steepest descent dynamical system with control. Applications to constrained minimization
نویسندگان
چکیده
منابع مشابه
Efficient perceptron learning using constrained steepest descent
An algorithm is proposed for training the single-layered perceptron. The algorithm follows successive steepest descent directions with respect to the perceptron cost function, taking care not to increase the number of misclassified patterns. The problem of finding these directions is stated as a quadratic programming task, to which a fast and effective solution is proposed. The resulting algori...
متن کاملFinsler Steepest Descent with Applications to Piecewise-regular Curve Evolution
This paper introduces a novel steepest descent flow in Banach spaces. This extends previous works on generalized gradient descent, notably the work of Charpiat et al. [12], to the setting of Finsler metrics. Such a generalized gradient allows one to take into account a prior on deformations (e.g., piecewise rigid) in order to favor some specific evolutions. We define a Finsler gradient descent ...
متن کاملEecient Perceptron Learning Using Constrained Steepest Descent Running Title: Eecient Perceptron Learning 1 Eecient Perceptron Learning Using Constrained Steepest Descent
| An algorithm is proposed for training the single-layered per-ceptron. The algorithm follows successive steepest descent directions with respect to the perceptron cost function, taking care not to increase the number of misclassiied patterns. The problem of nding these directions is stated as a quadratic programming task, to which a fast and eeective solution is proposed. The resulting algorit...
متن کاملConstrained Steepest Descent in the 2{Wasserstein Metric
We study several constrained variational problem in the 2–Wasserstein metric for which the set of probability densities satisfying the constraint is not closed. For example, given a probability density F0 on IR and a time–step h > 0, we seek to minimize I(F ) = hS(F ) + W 2 2 (F0, F ) over all of the probability densities F that have the same mean and variance as F0, where S(F ) is the entropy ...
متن کاملSteepest descent method for quasiconvex minimization on Riemannian manifolds
This paper extends the full convergence of the steepest descent algorithm with a generalized Armijo search and a proximal regularization to solve quasiconvex minimization problems defined on complete Riemannian manifolds. Previous convergence results are obtained as particular cases of our approach and some examples in non Euclidian spaces are given.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ESAIM: Control, Optimisation and Calculus of Variations
سال: 2004
ISSN: 1292-8119,1262-3377
DOI: 10.1051/cocv:2004005