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Gradient method

Known as: Gradient (disambiguation) 
In optimization, gradient method is an algorithm to solve problems of the form with the search directions defined by the gradient of the function at… Expand
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Related topics

Related topics

11 relations
AlgorithmBiconjugate gradient methodBiconjugate gradient stabilized methodConjugate gradient method
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Broader (1)

Numerical linear algebra

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
We consider the problem of minimizing the sum of two convex functions: one is the average of a large number of smooth component… Expand
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Highly Cited
2014
Highly Cited
2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
In this work we introduce a new optimisation method called SAGA in the spirit of SAG, SDCA, MISO and SVRG, a set of recently… Expand
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Highly Cited
2014
Highly Cited
2014
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
We derive a second-order ordinary differential equation (ODE), which is the limit of Nesterov's accelerated gradient method. This… Expand
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Highly Cited
2013
Highly Cited
2013
Gradient methods for minimizing composite functions
In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two… Expand
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Highly Cited
2012
Highly Cited
2012
A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets
We propose a new stochastic gradient method for optimizing the sum of a finite set of smooth functions, where the sum is strongly… Expand
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Highly Cited
2011
Highly Cited
2011
Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
We consider the problem of optimizing the sum of a smooth convex function and a non-smooth convex function using proximal… Expand
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Highly Cited
2009
Highly Cited
2009
An accelerated gradient method for trace norm minimization
We consider the minimization of a smooth loss function regularized by the trace norm of the matrix variable. Such formulation… Expand
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Highly Cited
2007
Highly Cited
2007
Gradient methods for minimizing composite objective function
In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two… Expand
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Highly Cited
2001
Highly Cited
2001
A Natural Policy Gradient
We provide a natural gradient method that represents the steepest descent direction based on the underlying structure of the… Expand
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Highly Cited
2000
Highly Cited
2000
Gradient Convergence in Gradient methods with Errors
We consider the gradient method $x_{t+1}=x_t+\g_t(s_t+w_t)$, where $s_t$ is a descent direction of a function $f:\rn\to\re$ and… Expand
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