Results 71 to 80 of about 109,092 (251)

Unveiling the Role of Curvature in Carbon for Improved Energy Release of Ammonium Perchlorate

Advanced Materials, EarlyView.
High‐curvature carbon materials identified via machine learning and simulation can enhance the heat release and combustion performance of ammonium perchlorate. ABSTRACT The catalytic role of carbon curvature in the thermal decomposition of ammonium perchlorate (AP) remains largely unexplored. To address this gap, this study employs machine learning and
Dan Liu, Keliang Song, Haorui Zhang, Zhipeng Liu, Guansong He, Junru Wang, Wenming Yang, Xu Zhao, Zhijian Yang   +8 more
wiley   +1 more source

A comparative analysis of hyperparameter optimization using LSTM-based deep learning models for urban air quality predictions

Ain Shams Engineering Journal
Air pollution poses significant threats to human health and the environment, necessitating accurate prediction models for effective management and mitigation strategies.
Beytullah Eren, Caner Erden, Ayşegül Atalı, Serkan Ozdemir   +3 more
doaj   +1 more source

Multi-Task Multicriteria Hyperparameter Optimization

, 2020
We present a new method for searching optimal hyperparameters among several tasks and several criteria. Multi-Task Multi Criteria method (MTMC) provides several Pareto-optimal solutions, among which one solution is selected with given criteria significance coefficients.
Akhmetzyanov, Kirill, Yuzhakov, Alexander   +1 more
openaire   +2 more sources

HPN: Personalized Federated Hyperparameter Optimization

, 2023
Numerous research studies in the field of federated learning (FL) have attempted to use personalization to address the heterogeneity among clients, one of FL's most crucial and challenging problems. However, existing works predominantly focus on tailoring models.
Cheng, Anda, Wang, Zhen, Li, Yaliang, Cheng, Jian   +3 more
openaire   +2 more sources

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets

, 2017
Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks.
Bartels, Simon, Falkner, Stefan, Hennig, Philipp, Hutter, Frank, Klein, Aaron   +4 more
core  

Hyperparameter Optimization: A Spectral Approach

, 2017
We give a simple, fast algorithm for hyperparameter optimization inspired by techniques from the analysis of Boolean functions. We focus on the high-dimensional regime where the canonical example is training a neural network with a large number of hyperparameters.
Hazan, Elad, Klivans, Adam, Yuan, Yang
openaire   +2 more sources

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction

Scientific Reports
Federated Learning is transforming electrical load forecasting by enabling Artificial Intelligence (AI) models to be trained directly on household edge devices.
Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas   +6 more
doaj   +1 more source

Evaluation of Hyperparameter Optimization Techniques for Traditional Machine Learning Models [PDF]

Jisuanji kexue
Reasonable hyperparameters ensure that machine learning models can adapt to different backgrounds and tasks.In order to avoid the inefficiency caused by manual adjustment of a large number of model hyperparameters and a vast search space,various ...
LI Haixia, SONG Danlei, KONG Jianing, SONG Yafei, CHANG Haiyan
doaj   +1 more source