Results 11 to 20 of about 174,537,063 (257)

On Type-I singularities in Ricci flow [PDF]

open access: yes, 2011
07.02.13 KB. Accepted version ok to add to Spiral. IP/Sherpa.We define several notions of singular set for Type I Ricci flows and show that they all coincide.
Topping, Peter   +5 more
core   +6 more sources

Comparing policy gradient and value function based reinforcement learning methods in simulated electrical power trade [PDF]

open access: yes, 2012
In electrical power engineering, reinforcement learning algorithms can be used to model the strategies of electricity market participants. However, traditional value function based reinforcement learning algorithms suffer from convergence issues when ...
Burt, Graeme   +7 more
core   +3 more sources

Accelerating Variance-Reduced Stochastic Gradient Methods [PDF]

open access: yes, 2022
Variance reduction is a crucial tool for improving the slow convergence of stochastic gradient descent. Only a few variance-reduced methods, however, have yet been shown to directly benefit from Nesterov’s acceleration techniques to match the convergence
Driggs, Derek   +3 more
core   +3 more sources

Randomized gradient-free methods in convex optimization [PDF]

open access: yes, 2023
This review presents modern gradient-free methods to solve convex optimization problems. By gradient-free methods, we mean those that use only (noisy) realizations of the objective value.
Dvurechensky, Pavel   +5 more
core   +1 more source

A continuous/discontinuous Galerkin formulation for a strain gradient-dependent damage model [PDF]

open access: yes, 2004
The numerical solution of strain gradient-dependent continuum problems has been hindered by continuity demands on the basis functions. The presence of terms in constitutive models that involve gradients of the strain field means that the $C^0$ continuity
G. N. Wells   +2 more
core   +6 more sources

Multi-element stochastic reduced basis methods [PDF]

open access: yes, 2007
This paper presents mutli-element Stochastic Reduced Basis Methods (ME-SRBMs) for solving linear stochastic partial differential equations. In ME-SRBMs, the domain of definition of the random inputs is decomposed into smaller subdomains or random ...
Surya Mohan, P.   +5 more
core   +1 more source

An approach to nonlinear viscoelasticity via metric gradient flows [PDF]

open access: yes, 2013
We formulate quasistatic nonlinear finite-strain viscoelasticity of rate type as a gradient system. Our focus is on nonlinear dissipation functionals and distances that are related to metrics on weak diffeomorphisms and that ensure time-dependent frame ...
Mielke, A.   +4 more
core   +1 more source

Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods [PDF]

open access: yes, 2022
With the purpose of examining biased updates in variance-reduced stochastic gradient methods, we introduce SVAG, a SAG/SAGA-like method with adjustable bias.
Giselsson, Pontus   +6 more
core   +1 more source

Accelerated Gradient Methods with Absolute and Relative Noise in the Gradient

open access: yes, 2023
In this paper, we investigate accelerated first-order methods for smooth convex optimization problems under inexact information on the gradient of the objective.
Dvurechensky, Pavel   +3 more
core   +1 more source

Comparative study on credibility measures of type-2 and type-1 fuzzy variables and their application to a multi-objective profit transportation problem via goal programming

open access: yesInternational Journal of Transportation Science and Technology, 2017
In real world applications supply, demand and transportation costs per unit of the quantities in multi-objective transportation problems may be hardly specified accurately because of the changing economic and environmental conditions.
Dipak Kumar Jana   +2 more
doaj   +1 more source

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