Search Results - Normalized proximal gradient algorithm

Hybrid SGD algorithms to solve stochastic composite optimization problems with application in sparse portfolio selection problems by Yang, Zhen-Ping, Zhao, Yong

“… The first algorithm is the prox-linear hybrid stochastic gradient algorithm, which may achieve sample complexities of O(ϵ2τ−5/2) and O(ϵτ−3/2…”
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Robotics-based vineyard water potential monitoring at high resolution by Saiz-Rubio, Verónica, Rovira-Más, Francisco, Cuenca-Cuenca, Andrés, Alves, Fernando

“… The purpose of this research is deploying a proximal sensing solution using non-invasive and cost-effective sensors onboard an Autonomous Ground Vehicle (AGV…”
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Using Remote and Proximal Sensing Data and Vine Vigor Parameters for Non-Destructive and Rapid Prediction of Grape Quality by Lyu, Hongyi, Grafton, Miles, Ramilan, Thiagarajah, Irwin, Matthew, Wei, Hsiang-En, Sandoval, Eduardo

“…), support vector regression (SVR), random forest regression (RFR), extreme gradient boosting (XGBoost…”
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Enhancing Cybersecurity in Industrial Control System with Autonomous Defense Using Normalized Proximal Policy Optimization Model by Xu, Shoukun, Xie, Zihao, Zhu, Chenyang, Wang, Xueyuan, Shi, Lin

“… We focus on evaluating value-based and policy gradient-based RL algorithms and propose enhancements to Proximal Policy Optimization (PPO…”
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Entropic Proximal Operators for Nonnegative Trigonometric Polynomials by Hsiao-Han Chao, Vandenberghe, Lieven

“… The methods are based on generalized proximal operators defined in terms of the Itakura-Saito distance…”
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Study on deep reinforcement learning for multi-task scheduling in cloud manufacturing by Xiao, Jiuhong, Cai, Yishuai, Chen, Yong

“… Despite the development of various meta-heuristic algorithms for cloud manufacturing multi-task scheduling (CMMS…”
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Proximal policy optimization with reward-based prioritization by Zheng, Mingsheng, Zhang, Junwei, Zhan, Changshuai, Ren, Xinyu, Lü, Shuai

“…The PPO (Proximal Policy Optimization) algorithm is a policy optimization-based deep reinforcement learning algorithm that has achieved outstanding results and widespread applications…”
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Improving wheat yield prediction integrating proximal sensing and weather data with machine learning by Ruan, Guojie, Li, Xinyu, Yuan, Fei, Cammarano, Davide, Ata-UI-Karim, Syed Tahir, Liu, Xiaojun, Tian, Yongchao, Zhu, Yan, Cao, Weixing, Cao, Qiang

“…•Normalized Difference Red Edge Index was the most contributory features.•Average temperature, minimum temperature, and relative humidity were key weather data…”
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A Riemannian Optimization Approach to Clustering Problems by Huang, Wen, Wei, Meng, Gallivan, Kyle A., Van Dooren, Paul

“… A Riemannian proximal gradient method that allows an adaptive step size is proposed. The proposed Riemannian proximal gradient method solves its subproblem inexactly and still guarantees its global convergence…”
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Discrete Aware Matrix Completion via Convexized \ell-Norm Approximation by Fuhrling, Niclas, Ando, Kengo, Freitas De Abreu, Giuseppe Thadeu, G., David Gonzalez, Gonsa, Osvaldo

“…) under a proximal gradient (PG) framework. Simulation results demonstrate the superior performance of the new method compared to the SotA techniques as well as the earlier \ell_{1} -norm-based discrete-aware matrix completion approach…”
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Elevating Facial Expression Detection: Empowered by VGG-19 and Weight-Normalized Gradient Boost Algorithm by M, Rajeshwari, K, Krishna Prasad

“…Facial expression recognition termed as FER, is one of the vital tasks which is able in mimicking the human ability and wellness. Face expression and other…”
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Preferential Proximal Policy Optimization by Balasuntharam, Tamilselvan, Davoudi, Heidar, Ebrahimi, Mehran

“…The Proximal Policy Optimization (PPO) is a policy gradient approach providing state-of-the-art performance in many domains through the "surrogate" objective function using stochastic gradient ascent…”
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Prediction of soil fertility properties in Southern Brazil via proximal sensing by NACHTIGALL, STEFAN D., MANCINI, MARCELO, REIS, RENATA A., ARAÚJO, ELIAS FRANK DE, CARNEIRO, MARCO AURÉLIO C., CURI, NILTON, SILVA, SÉRGIO HENRIQUE GODINHO

“…Abstract Although proximal sensing coupled with machine learning (ML) algorithms have been successful for characterizing soils, questions remain regarding their effectiveness under varied soil conditions…”
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Iterative Reconstrained Low-Rank Representation via Weighted Nonconvex Regularizer by Zheng, Jianwei, Lu, Cheng, Yu, Hongchuan, Wang, Wanliang, Chen, Shengyong

“…Benefiting from the joint consideration of geometric structures and low-rank constraint, graph low-rank representation (GLRR) method has led to the…”
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Efficient Dictionary-Refining Kernel Adaptive Filter With Fundamental Insights by Takizawa, Masa-aki, Yukawa, Masahiro

“…First, we study a basic kernel adaptive filtering algorithm based on stochastic restricted-gradient, which is a natural extension of the naive online regularized risk minimization algorithm (NORMA…”
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Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition by Jewan, Shaikh, Gautam, Deepak, Sparkes, Debbie, Singh, Ajit, Billa, Lawal, Cogato, Alessia, Murchie, Erik, Pagay, Vinay

“…) algorithms could overcome these challenges. Our study aimed to assess the potential of multimodal data…”
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Corn Nitrogen Status Diagnosis with an Innovative Multi-Parameter Crop Circle Phenom Sensing System by Cummings, Cadan, Miao, Yuxin, Paiao, Gabriel Dias, Kang, Shujiang, Fernández, Fabián G.

“… The Crop Circle Phenom sensor is a new integrated multi-parameter proximal ACS system for in-field plant phenomics with the capability to measure reflectance, structural, and climatic attributes…”
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High-resolution elemental mapping of the root-rhizosphere-soil continuum using laser-induced breakdown spectroscopy (LIBS) by Ilhardt, Peter D., Nuñez, Jamie R., Denis, Elizabeth H., Rosnow, Joshua J., Krogstad, Eirik J., Renslow, Ryan S., Moran, James J.

“…Understanding the complex chemical nature of root-soil interactions is essential for building the next generation of sustainable agricultural systems and…”
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Toward Self-Driving Bicycles Using State-of-the-Art Deep Reinforcement Learning Algorithms by Choi, SeungYoon, Le, Tuyen P., Nguyen, Quang D., Layek, Md Abu, Lee, SeungGwan, Chung, TaeChoong

“…) and Proximal Policy Optimization (PPO). For the performance evaluation, we implemented the proposed algorithm in various settings such as fixed and random speed, start…”
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Improving Steady-State Performance of the UT-ZA-PNLMS Algorithm for Sparse Systems by Anudeep, K Sesha Sai, Khoria, Kuldeep, Das, Rajib Lochan

“…For identifying sparse systems, a recently proposed algorithm called upper threshold based zero attracting proportionate normalized least mean square (UT-ZA-PNLMS…”
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