Results 11 to 20 of about 167,180,107 (247)
On Type-I singularities in Ricci flow [PDF]
, 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
A continuous/discontinuous Galerkin formulation for a strain gradient-dependent damage model [PDF]
, 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 +11 more sources
Comparing policy gradient and value function based reinforcement learning methods in simulated electrical power trade [PDF]
, 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 +4 more sources
Accelerating Variance-Reduced Stochastic Gradient Methods [PDF]
, 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 +2 more
core +3 more sources
Randomized gradient-free methods in convex optimization [PDF]
, 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
Multi-element stochastic reduced basis methods [PDF]
, 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]
, 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
BMC Cardiovascular Disorders, 2023 Background Impaired left ventricular function is an independent predictor of adverse clinical outcomes in patients with aortic stenosis. The aim of this study is to evaluate the short-term changes of echocardiographic parameters, New York Heart ...
Mei Dong +7 more
doaj +1 more source
Inexact reduced gradient methods in nonconvex optimization [PDF]
, 2022 This paper proposes and develops new linesearch methods with inexact gradient information for finding stationary points of nonconvex continuously differentiable functions on finite-dimensional spaces.
Khanh, Pham Duy +2 more
core +1 more source
Improvement of conjugate gradient methods for removing impulse noise images [PDF]
, 2023 Optimization problems occur in most disciplines like engineering, physics, mathematics, economics, administration, commerce, social sciences, and even politics.
Ahmed A. Abdullah, Ali +3 more
core +1 more source