Results 61 to 70 of about 28,952 (292)
Adaptive Step Sizes for Stochastic Gradient Descent
, 2023 In this thesis, we first lay some theoretical groundwork before motivating and discussing the stochastic gradient descent method along with its variations. We then analyze some popular step size strategies with a focus on the stochastic Polyak step size,
Karakoc, Dylan
core
Stability and Generalization of Decentralized Stochastic Gradient Descent
, 2021 The stability and generalization of stochastic gradient-based methods provide valuable insights into understanding the algorithmic performance of machine learning models.
Li, Dongsheng, Wang, Bao, Sun, Tao
core +1 more source
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Adaptive gradient descent for convex and non-convex stochastic optimization [PDF]
, 2019 In this paper we propose several adaptive gradient methods for stochastic optimization. Our methods are based on Armijo-type line search and they simultaneously adapt to the unknown Lipschitz constant of the gradient and variance of the stochastic ...
Dvurechensky, Pavel +4 more
core +1 more source
Field detection of small pests through stochastic gradient descent with genetic algorithm
, 2023 Pest invasion is one of the main reasons that affect crop yield and quality. Therefore, accurate detection of pests is a key technology of smart agriculture. Pests often exist as small objects with limited features in the actual field.
Yaxiong Chen +13 more
core +1 more source
Advanced Engineering Materials, EarlyView.This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele +2 more
wiley +1 more source
Distributed Stochastic Gradient Descent With Compressed and Skipped Communication
IEEE Access, 2023 This paper introduces CompSkipDSGD, a new algorithm for distributed stochastic gradient descent that aims to improve communication efficiency by compressing and selectively skipping communication.
Tran Thi Phuong +2 more
doaj +1 more source
Stochastic Adaptive Gradient Descent Without Descent
CoRRWe introduce a new adaptive step-size strategy for convex optimization with stochastic gradient that exploits the local geometry of the objective function only by means of a first-order stochastic oracle and without any hyper-parameter tuning. The method comes from a theoretically-grounded adaptation of the Adaptive Gradient Descent Without Descent ...
Jean-François Aujol +2 more
openaire +2 more sources
On Scalable Inference with Stochastic Gradient Descent
CoRR, 2017 In many applications involving large dataset or online updating, stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates and has gained increasing popularity due to its numerical convenience and memory efficiency. While the asymptotic properties of SGD-based estimators have been established decades ago, statistical ...
Yixin Fang, Jinfeng Xu, Lei Yang
openaire +2 more sources
Advanced Engineering Materials, EarlyView.A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi +3 more
wiley +1 more source