Results 41 to 50 of about 32,654 (268)

Scalable Privacy-Compliant Virality Prediction on Twitter [PDF]

, 2019
The digital town hall of Twitter becomes a preferred medium of communication for individuals and organizations across the globe. Some of them reach audiences of millions, while others struggle to get noticed.
Kowalczyk, Damian Konrad, Larsen, Jan
core   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source

Block-distributed Gradient Boosted Trees

, 2019
The Gradient Boosted Tree (GBT) algorithm is one of the most popular machine learning algorithms used in production, for tasks that include Click-Through Rate (CTR) prediction and learning-to-rank.
Bühlmann Peter, Chen Tianqi, Ke Guolin, Li Mu   +3 more
core   +1 more source

Ensemble Machine Learning of Gradient Boosting (XGBoost, LightGBM, CatBoost) and Attention-Based CNN-LSTM for Harmful Algal Blooms Forecasting

Toxins, 2023
Harmful algal blooms (HABs) are a serious threat to ecosystems and human health. The accurate prediction of HABs is crucial for their proactive preparation and management. While mechanism-based numerical modeling, such as the Environmental Fluid Dynamics
Jung Min Ahn, Jungwook Kim, Kyunghyun Kim   +2 more
semanticscholar   +1 more source

Application of an improved LightGBM hybrid integration model combining gradient harmonization and Jacobian regularization for breast cancer diagnosis

Scientific Reports
Cancer, as a shocking disease, is one of the most common malignant tumors among women, posing a huge threat to the physical health and safety of women worldwide.
Xiaoyan Sun
semanticscholar   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Personal bankruptcy prediction using machine learning techniques

Economics and Business Review
It has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies.
Brygała Magdalena, Korol Tomasz
doaj   +1 more source

Landslide susceptibility evaluation considering the importance selection of influencing factors and soil moisture content

Shuiwen dizhi gongcheng dizhi
The current landslide susceptibility assessment system lacks unified and scientifically grounded standards for selecting factors that influence landslide development, leading to inconsistencies in evaluation results.
Zhongyu WANG, Sumin LI, Liwei YUAN, Weipeng LE   +3 more
doaj   +1 more source

Comparing the Performance of Algorithmic Trading Systems based on Machine Learning in the Cryptocurrency Market [PDF]

راهبرد مدیریت مالی
The purpose of this research is to use the ensemble learning model to combine the predictions of random forest models, short-term long memory and recurrent neural network to provide an algorithmic trading system based on its.
Emad Koosha, Mohsen Seighaly, Ebrahim Abbasi   +2 more
doaj   +1 more source

A Semi-Supervised Abbreviation Disambiguation Method Based on ACNN and Bi-LSTM

Journal of Harbin University of Science and Technology, 2022
In order to improve disambiguation accuracy of biomedical abbreviations， a semi-supervised abbreviation disambiguation method based on asymmetric convolutional neural networks and bidirectional long short term memory networks is proposed. Abbreviation is
ZHANG Chun-xiang, PANG Shu-yang, GAO Xue-yao   +2 more
doaj   +1 more source