Results 91 to 100 of about 36,835 (256)

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Tuning the Tuner: Introducing Hyperparameter Optimization for Auto-Tuning

2025 IEEE International Conference on eScience (eScience)
Automatic performance tuning (auto-tuning) is widely used to optimize performance-critical applications across many scientific domains by finding the best program variant among many choices. Efficient optimization algorithms are crucial for navigating the vast and complex search spaces in auto-tuning. As is well known in the context of machine learning
Willemsen, F-.J., Nieuwpoort, R.V. van, Werkhoven, B.J.C. van   +2 more
openaire   +3 more sources

Hate speech detection using pretrained DeBERTaV3 optimized with Grey Wolf Optimizer: a hybrid approach for social media content moderation

Scientific Reports
The proliferation of hate speech on social media poses a significant challenge to maintaining safe and inclusive online environments, necessitating accurate and scalable automated detection systems.
Manas Kamal Das, Basil Skaria, Argha Auddy, M. Vidhyalakshmi   +3 more
doaj   +1 more source

Artificial Intelligence‐Based Body Composition Analysis Reveals Sex‐Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study

Advanced Science, EarlyView.
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li, Tingting Liu, Qian Yang, Zhiqing Zhang, Xiaofang Guo, Xiang Wang, Yihan Zhang, Limin Ge, Yu Su, Wenjun Wu, Weihua Guo, Zheng Wang, Lian Yang, Yanfeng Niu   +13 more
wiley   +1 more source

Efficient Q-learning hyperparameter tuning using FOX optimization algorithm

Results in Engineering
Reinforcement learning is a branch of artificial intelligence in which agents learn optimal actions through interactions with their environment. Hyperparameter tuning is crucial for optimizing reinforcement learning algorithms and involves the selection ...
Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid   +2 more
doaj   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

Hyperparameter Tuning and Optimization Applications

, 2023
AbstractThis chapter reflects on advantages and sense of use of Hyperparameter Tuning (HPT) and its disadvantages. In particular it shows how important it is, to keep the human in the loop, even if HPT works perfectly. The chapter presents a collection of HPT studies. First, HPT applications in Machine Learning (ML) and Deep Learning (DL) are described.
openaire   +1 more source

SciBERT Optimisation for Named Entity Recognition on NCBI Disease Corpus with Hyperparameter Tuning

Journal of Applied Informatics and Computing
Named Entity Recognition (NER) in the biomedical domain faces complex challenges due to the variety of medical terms and their context of use. Transformer-based models, such as SciBERT, have proven to be effective in natural language processing (NLP ...
Abu Salam, Syaiful Rizal Sidiq
doaj   +1 more source

Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design

Advanced Science, EarlyView.
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng, Chuyi Liu, Zhaoming Liu, Mao Su, Chenyu Tang, Xiang Zheng, Hao Zhang, Jingyuan Li   +7 more
wiley   +1 more source

Hyperparameter Optimization and Feature Selection Analysis on the XGBoost Model for Hepatitis C Infection Prediction

Journal of Applied Informatics and Computing
Hepatitis C is a liver disease that can progress to chronic conditions such as cirrhosis and liver cancer. Early detection is essential and can be supported through machine learning approaches.
Nadia Martha Lefi, Majid Rahardi
doaj   +1 more source