Search Results - stochastic/gradient-based optimization algorithm~

A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems by Curtis, Frank E, Kungurtsev, Vyacheslav, Robinson, Daniel P, Wang, Qi

“…A stochastic-gradient-based interior-point algorithm for minimizing a continuously differentiable objective function…”
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Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks by Moya, Christian, Lin, Guang

“…The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings…”
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Quasi-Newton optimised Kolmogorov-Arnold Networks for wind farm power prediction by Mubarak, Auwalu Saleh, Ameen, Zubaida Said, Mati, Sagiru, Lasisi, Ayodele, Naveed, Quadri Noorulhasan, Abdulkadir, Rabiu Aliyu

“…Having accurate and effective wind energy forecasting that can be easily incorporated into smart networks is important. Appropriate planning and energy…”
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Topology optimization under uncertainty using a stochastic gradient-based approach by De, Subhayan, Hampton, Jerrad, Maute, Kurt, Doostan, Alireza

“… Most traditional TOuU methods use gradient-based optimization algorithms and rely on accurate estimates of the statistical moments and their gradients, e.g…”
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Improving Deep Neural Networks' Training for Image Classification With Nonlinear Conjugate Gradient-Style Adaptive Momentum by Wang, Bao, Ye, Qiang

“…Momentum is crucial in stochastic gradient-based optimization algorithms for accelerating or improving training deep neural networks (DNNs…”
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Stochastic gradient-based fast distributed multi-energy management for an industrial park with temporally-coupled constraints by Zhu, Dafeng, Yang, Bo, Ma, Chengbin, Wang, Zhaojian, Zhu, Shanying, Ma, Kai, Guan, Xinping

“… Specifically to achieve charging/discharging constraints due to storage and short-term energy balancing, a fast distributed algorithm based on stochastic gradient with two-timescale implementation…”
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Stochastic Gradient-Based Optimal Signal Control With Energy Consumption Bounds by Bin Al Islam, S. M. A., Abdul Aziz, H. M., Hajbabaie, Ali

“…This paper develops a stochastic gradient-based optimization model for traffic signal control with bounds on network-level vehicular energy consumption…”
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Multi-stage stochastic gradient method with momentum acceleration by Luo, Zhijian, Chen, Siyu, Qian, Yuntao, Hou, Yueen

“… Momentum acceleration technique is famously known for building gradient-based algorithms with fast convergence in large-scale optimization…”
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A stochastic gradient-based two-step sparse identification algorithm for multivariate ARX systems by Fu, Yanxin, Zhao, Wenxiao

“… We propose a two-step algorithm, where in the first step the stochastic gradient (SG) algorithm is applied to obtain initial estimates of the unknown parameter matrix…”
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Edge-Based Stochastic Gradient Algorithm for Distributed Optimization by Wang, Zheng, Li, Huaqing

“… An augmented Lagrange (AL) stochastic gradient algorithm is presented to address the distributed optimization problem, which is integrated with the factorization of weighted Laplacian and local unbiased stochastic averaging gradient methods…”
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DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference in Image Recognition by Xie, Jiyang, Ma, Zhanyu, Xue, Jing-Hao, Zhang, Guoqiang, Sun, Jian, Zheng, Yinhe, Guo, Jun

“… In addition, we propose a dual-supervised stochastic gradient-based variational Bayes (DS-SGVB) algorithm for the MoGMM-FC layer optimization…”
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Cross-Entropy Optimization for Hyperparameter Optimization in Stochastic Gradient-based Approaches to Train Deep Neural Networks by Li, Kevin, Li, Fulu

“…In this paper, we present a cross-entropy optimization method for hyperparameter optimization in stochastic gradient-based approaches to train deep neural networks…”
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Motion correction in CEST MRI series exploiting Adaptive Stochastic Gradient Descent (ASGD) - based optimization algorithm by Liang, Yuhua, Bie, Chongxue, Chen, Bowei, Hou, Yuqing, Song, Xiaolei

“…) MRI series was introduced in this paper. The method was based on adaptive stochastic gradient descent optimization (ASGD…”
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A similarity-based Bayesian mixture-of-experts model by Zhang, Tianfang, Bokrantz, Rasmus, Olsson, Jimmy

“… Posterior inference is performed on the parameters of the mixture components as well as the distance metric using a mean-field variational Bayes algorithm accompanied with a stochastic gradient-based…”
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Step Size Adaptation for Accelerated Stochastic Momentum Algorithm Using SDE Modeling and Lyapunov Drift Minimization by Yuan, Yulan, Tsang, Danny H. K., Lau, Vincent K. N.

“…Training machine learning models often involves solving high-dimensional stochastic optimization problems, where stochastic gradient-based algorithms are hindered by slow convergence…”
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Lyapunov-based Optimization of Edge Resources for Energy-Efficient Adaptive Federated Learning by Battiloro, Claudio, Lorenzo, Paolo Di, Merluzzi, Mattia, Barbarossa, Sergio

“… We consider a set of devices collecting local data and uploading processed information to an edge server, which runs stochastic gradient-based algorithms to perform continuous learning and adaptation…”
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An Adaptive Stochastic Gradient Algorithm Based on FISTA for Convex Optimization by Zhai, Yujia, Xue, Dan, Qi, Rulei, Wang, Zewei

“…In this paper, we propose a fast iterative stochastic gradient method to solve convex optimization problem, referred as the RFISTA-SVRG-TR…”
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A uniform momentum-based distributed stochastic gradient tracking algorithm for non-convex optimization by Li, Yantao, Wu, Chaoxu, Chen, Yingjue, Zhang, Keke, Lü, Qingguo, Deng, Shaojiang, Li, Huaqing

“…This paper investigates distributed non-convex optimization problems, specifically focusing on a collaborative approach to optimize a global non-convex objective function across agents over networks…”
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An Edge-based Stochastic Proximal Gradient Algorithm for Decentralized Composite Optimization by Zhang, Ling, Yan, Yu, Wang, Zheng, Li, Huaqing

“…This paper investigates decentralized composite optimization problems involving a common non-smooth regularization term over an undirected and connected network…”
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Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs by Goda, Takashi, Hironaka, Tomohiko, Kitade, Wataru, Foster, Adam

“…In this paper we propose an efficient stochastic optimization algorithm to search for Bayesian experimental designs such that the expected information gain is maximized…”
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