Results 41 to 50 of about 98,022 (269)
Advanced Functional Materials, EarlyView.A chiral photodetector capable of selectively distinguishing left‐ and right‐handed circularly polarized light is experimentally demonstrated. The device, which features a nanopatterned electrode inverse‐designed by a genetic algorithm within a metal–dielectric–metal nanocavity that incorporates a vacuum‐deposited small‐molecule multilayer, exhibits ...
Kyung Ryoul Park +3 more
wiley +1 more source
Research and Analysis of IndoBERT Hyperparameter Tuning in Fake News Detection
Jurnal Nasional Teknik Elektro dan Teknologi InformasiThe rapid advancement of communication technology has transformed how information is shared, but it has also brought concerns about the proliferation of false information.
Anugerah Simanjuntak +6 more
doaj +1 more source
Comparative additive manufacturing defect prediction accuracy with a few transfer learning implementations of deep learning models [PDF]
EPJ Web of ConferencesThis paper addresses the problem of a comprehensive quality assurance strategy for additively manufactured components with integrated in-situ inspection and artificial intelligence and machine learning (AIML) models.
Bajpai Anamol +3 more
doaj +1 more source
Hyperparameter Tuning with Renyi Differential Privacy
, 2021 For many differentially private algorithms, such as the prominent noisy stochastic gradient descent (DP-SGD), the analysis needed to bound the privacy leakage of a single training run is well understood. However, few studies have reasoned about the privacy leakage resulting from the multiple training runs needed to fine tune the value of the training ...
Papernot, Nicolas, Steinke, Thomas
openaire +2 more sources
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
Advanced Functional Materials, EarlyView.An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
Evaluasi Performa XGBoost dengan Oversampling dan Hyperparameter Tuning untuk Prediksi Alzheimer
Techno.ComAlzheimer adalah gangguan neurodegeneratif yang mempengaruhi kemampuan kognitif dan memori, deteksi dini sangat penting untuk pengobatan yang tepat. Namun, untuk mendeteksi Alzheimer memerlukan biaya yang tinggi, sehingga penggunaan machine learning bisa
Furqon Nurbaril Yahya +2 more
doaj +1 more source
SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization
, 2018 Computer vision is experiencing an AI renaissance, in which machine learning models are expediting important breakthroughs in academic research and commercial applications.
Kinnison, Jeff +3 more
core +1 more source
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Bayesian Nonlinear Support Vector Machines for Big Data
, 2017 We propose a fast inference method for Bayesian nonlinear support vector machines that leverages stochastic variational inference and inducing points. Our experiments show that the proposed method is faster than competing Bayesian approaches and scales ...
Deutsch, Matthaeus +3 more
core +1 more source