Results 121 to 130 of about 93,556 (252)

FedPop: Federated Population-based Hyperparameter Tuning

Proceedings of the AAAI Conference on Artificial Intelligence
Federated Learning (FL) is a distributed machine learning (ML) paradigm, in which multiple clients collaboratively train ML models without centralizing their local data. Similar to conventional ML pipelines, the client local optimization and server aggregation procedure in FL are sensitive to the hyperparameter (HP) selection.
Chen, Haokun, Krompass, Denis, Gu, Jindong, Tresp, Volker   +3 more
openaire   +2 more sources

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Metaheuristics Approach for Hyperparameter Tuning of Convolutional Neural Network

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Deep learning is an artificial intelligence technique that has been used for various tasks. Deep learning performance is determined by its hyperparameter, architecture, and training (connection weight and bias).
Hindriyanto Purnomo, Tad Gonsalves, Evangs Mailoa, Fian Julio Santoso, Muhammad Rizky Pribadi   +4 more
doaj   +1 more source

Taming hyperparameter tuning in continuous normalizing flows using the JKO scheme. [PDF]

Sci Rep, 2023
Vidal A, Wu Fung S, Tenorio L, Osher S, Nurbekyan L.   +4 more
europepmc   +1 more source

Interlayer Dzyaloshinskii–Moriya Interaction in Synthetic Ferrimagnets for Spiking Neural Networks

Advanced Science, EarlyView.
This work introduces a groundbreaking integration of asymmetric magnetic structures (synthetic ferrimagnets) and antisymmetric magnetic interaction (interlayer Dzyaloshinskii–Moriya interaction) for the first time. It addresses the critical challenge of IL‐DMI detection and shows the discovery of unprecedented analog‐like spin‐orbit torque switching ...
Shen Li, Xing Chen, Mouad Fattouhi, Tianxun Huang, Chen Lv, Mark C. H. de Jong, Pingzhi Li, Daoqian Zhu, Xiaoyang Lin, Felipe Garcia‐Sanchez, Eduardo Martinez, Stéphane Mangin, Bert Koopmans, Weisheng Zhao, Reinoud Lavrijsen   +14 more
wiley   +1 more source

Optimizing Hyperparameter Tuning in Machine Learning to Improve the Predictive Performance of Cross-Species N6-Methyladenosine Sites. [PDF]

ACS Omega, 2023
Le NQK, Xu L.
europepmc   +1 more source

Nanozymes Integrated Biochips Toward Smart Detection System

Advanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen, Wang Zheng, Zhihui Zhang, Shenping Yu, Xinxin Hang, Han Wu, Xiao‐Wei Xiang, Wei Mu, Yanli Jiao, Zaizai Dong, Lingqian Chang   +10 more
wiley   +1 more source

Optimizing Image Classification: Automated Deep Learning Architecture Crafting with Network and Learning Hyperparameter Tuning. [PDF]

Biomimetics (Basel), 2023
Ang KM, Lim WH, Tiang SS, Sharma A, Eid MM, Tawfeek SM, Khafaga DS, Alharbi AH, Abdelhamid AA.   +8 more
europepmc   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy. [PDF]

World J Gastroenterol, 2022
Dalal S, Onyema EM, Malik A.
europepmc   +1 more source