Results 41 to 50 of about 36,010,976 (311)
Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold
SIAM Journal on Optimization, 2018 We consider optimization problems over the Stiefel manifold whose objective function is the summation of a smooth function and a nonsmooth function. Existing methods for solving this kind of problems can be classified into three classes.
Shixiang Chen +3 more
semanticscholar +1 more source
Frequency Analysis of Gradient Estimators in Volume Rendering [PDF]
, 1995 Gradient information is used in volume rendering to classify and color samples along a ray. In this paper, we present an analysis of the theoretically ideal gradient estimator and compare it to some commonly used gradient estimators.
Bentum, Mark J. +2 more
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Numerical Study of a Particle Method for Gradient Flows [PDF]
, 2016 We study the numerical behaviour of a particle method for gradient flows involving linear and nonlinear diffusion. This method relies on the discretisation of the energy via non-overlapping balls centred at the particles.
Carrillo, J. A. +3 more
core +4 more sources
A Gradient Method for Multilevel Optimization
CoRR, 2021 Although application examples of multilevel optimization have already been discussed since the 1990s, the development of solution methods was almost limited to bilevel cases due to the difficulty of the problem. In recent years, in machine learning, Franceschi et al.
Ryo Sato, Mirai Tanaka, Akiko Takeda
openaire +3 more sources
On the linear convergence of the stochastic gradient method with constant step-size [PDF]
, 2018 The strong growth condition (SGC) is known to be a sufficient condition for linear convergence of the stochastic gradient method using a constant step-size $\gamma$ (SGM-CS).
Cevher, Volkan, Vu, Bang Cong
core +2 more sources
Generalizing the Optimized Gradient Method for Smooth Convex Minimization [PDF]
SIAM Journal on Optimization, 2016 This paper generalizes the optimized gradient method (OGM) [Y. Drori and M. Teboulle, Math. Program., 145 (2014), pp. 451--482], [D. Kim and J. A. Fessler, Math. Program., 159 (2016), pp.
Donghwan Kim, J. Fessler
semanticscholar +1 more source
A Numerical Model to Estimate the Soil Thermal Conductivity Using Field Experimental Data
Applied Sciences, 2019 Soil thermal conductivity is an important parameter for understanding soil heat transfer. It is difficult to measure in situ with available instruments.
Leugim Corteze Romio +4 more
doaj +1 more source
The Convergence of Sparsified Gradient Methods
CoRR, 2018 Distributed training of massive machine learning models, in particular deep neural networks, via Stochastic Gradient Descent (SGD) is becoming commonplace. Several families of communication-reduction methods, such as quantization, large-batch methods, and gradient sparsification, have been proposed. To date, gradient sparsification methods - where each
Alistarh, Dan-Adrian +5 more
openaire +4 more sources
Model Based Optimisation Algorithm for Maximum Power Point Tracking in Photovoltaic Panels
Energies, 2020 Extracting maximum energy from photovoltaic (PV) systems at varying conditions is crucial. It represents a problem that is being addressed by researchers who are using several techniques to obtain optimal outcomes in real-life scenarios.
Faiçal Hamidi +6 more
doaj +1 more source
Curvature-aided Incremental Aggregated Gradient Method
, 2017 We propose a new algorithm for finite sum optimization which we call the curvature-aided incremental aggregated gradient (CIAG) method. Motivated by the problem of training a classifier for a d-dimensional problem, where the number of training data is $m$
Nedic, Angelia +3 more
core +1 more source