Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
6d
Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing
A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...
Abstract: As fake news spreads rapidly in social media, attempts to develop detection technology to automatically identify fake news are actively being developed, recently. However, most of them focus ...
Freshwater ecosystems worldwide have been suffering from declining oxygen levels—a trend known as deoxygenation—that ...
This study proposes a novel method for designing prosthetic heart valves (PHVs) by combining machine learning (ML) with optimization algorithms. This approach aims to overcome the limitations of ...
Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random forest [RF], support vector machine [SVM], and k-nearest neighbor ...
Abstract: In online advertising, click fraud poses a significant challenge, draining budgets and threatening the industry’s integrity by redirecting funds away from legitimate advertisers. Despite ...
But unlike most quants, I run a concentrated, fundamentals-based portfolio. More than 50% of my fund is invested in only eight companies, and they're the kinds of stocks that Peter Lynch and Charlie ...
Machine learning algorithms create potentially more accurate models than linear models, but any increase in accuracy over more traditional, better-understood, and more easily explainable techniques is ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results