New research shows mutual funds using machine learning strategies generate significant outperformance over traditional funds ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

With a notable absence of fresh corporate announcements, AppLovin shares have begun the week on a subdued note. This quiet ...

Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...

If you’ve ever chanced a gym training session during peak hours you’ll know it’s pot luck whether you can get your hands on the equipment you’re intending to use or not. There will almost certainly be ...

Traditional bibliometric approaches to research impact assessment have predominantly relied on citation counts, overlooking the qualitative dimensions of how research is received and discussed.

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Abstract: Multimodal sentiment analysis has garnered increasing attention. The bulk of existing work in multimodal sentiment analysis primarily focuses on designing various networks to align and ...

Multimodal sentiment analysis (MSA) is an emerging technology that seeks to digitally automate extraction and prediction of human sentiments from text, audio, and video. With advances in deep learning ...

Please provide your email address to receive an email when new articles are posted on . Researchers are using machine learning to identify data-driven PCOS subtypes. Findings may lead to more precise ...