نتایج جستجو برای: hybrid steepest
تعداد نتایج: 193167 فیلتر نتایج به سال:
The exact steepest descent method was born in [AKT4] by combining the ordinary steepest descent method with the exact WKB analysis. (See, e.g., [AKT2] for the notion and notations of the exact WKB analysis used in this report.) It is a straightforward generalization of the ordinary steepest descent method and provides us with a new powerful tool for the description of Stokes curves as well as f...
A novel learning methodology based on a hybrid mechanism for training interval singleton type-2 Takagi-SugenoKang fuzzy logic systems uses recursive orthogonal least-squares to tune the type-1 consequent parameters and the steepest descent method to tune the interval type-2 antecedent parameters. The proposed hybrid-learning algorithm changes the interval type-2 model parameters adaptively to m...
We propose a new selection rule for the coordinate selection in coordinate descent methods for huge-scale optimization. The efficiency of this novel scheme is provably better than the efficiency of uniformly random selection, and can reach the efficiency of steepest coordinate descent (SCD), enabling an acceleration of a factor of up to n, the number of coordinates. In many practical applicatio...
Steepest descent preconditioning is considered for the recently proposed nonlinear generalized minimal residual (N-GMRES) optimization algorithm for unconstrained nonlinear optimization. Two steepest descent preconditioning variants are proposed. The first employs a line search, while the second employs a predefined small step. A simple global convergence proof is provided for the NGMRES optimi...
Quantum machine learning aims to release the prowess of quantum computing improve methods. By combining methods with classical neural network techniques we aim foster an increase performance in solving classification problems. Our algorithm is designed for existing and near-term devices. We propose a novel hybrid variational classifier that combines gradient descent method steepest optimise par...
Steepest descent drives both theory and practice of nonsmooth optimization. We study slight relaxations of two influential notions of steepest descent curves — curves of maximal slope and solutions to evolution equations. In particular, we provide a simple proof showing that lower-semicontinuous functions that are locally Lipschitz continuous on their domains — functions playing a central role ...
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