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On the determination of epsilon during discriminative GMM training
(2010-12-01)
Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. ...
On the determination of epsilon during discriminative GMM training
(2010-12-01)
Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. ...
A NUMERICAL DESCENT METHOD FOR AN INVERSE PROBLEM OF A SCALAR CONSERVATION LAW MODELLING SEDIMENTATION
(SPRINGER, 2008)
This contribution presents a numerical descent method for the identification of parameters in the flux function of a scalar nonlinear conservation law when the solution at a fixed time is known. This problem occurs in a ...
A NUMERICAL DESCENT METHOD FOR AN INVERSE PROBLEM OF A SCALAR CONSERVATION LAW MODELLING SEDIMENTATION
(SPRINGER, 2006)
This contribution presents a numerical descent method for the identification of parameters in the flux function of a scalar nonlinear conservation law when the solution at a fixed time is known. This problem occurs in a ...
Gradient method with retards and generalizations
(Siam PublicationsPhiladelphiaEUA, 1998)
Cooperative concurrent asynchronous computation of the solution of symmetric linear systems
(Springer, 2017-07)
This paper extends the idea of Brezinski's hybrid acceleration procedure, for the solution of a system of linear equations with a symmetric coefficient matrix of dimension n, to a new context called cooperative computation, ...
SPECTRAL PROJECTED GRADIENT METHOD WITH INEXACT RESTORATION FOR MINIMIZATION WITH NONCONVEX CONSTRAINTS
(Siam PublicationsPhiladelphiaEUA, 2009)
A continuous-time model of stochastic gradient descent: convergence rates and complexities under Lojasiewicz inequality
(Universidad de Chile, 2021)
In this thesis we study the convergence rates and complexities of a continuous model of the Stochastic Gradient Descent (SGD) under convexity, strong convexity and Łojasiewicz assumptions, the latter being a way to generalize ...
A Robust Predictive Speed Control for SPMSM Systems Using a Sliding Mode Gradient Descent Disturbance Observer
(2023-03-01)
This paper proposes a sliding mode gradient descent disturbance observer-based adaptive reaching law sliding mode predictive speed control (GD-SMPC+ARL) for surface-mounted permanent magnet synchronous motor (SPMSM) systems ...