AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
IEEE

Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm

Abstract: Reducing energy consumption has become a pressing need for modern machine learning, which has achieved many of its most impressive results by scaling to larger and more energy-consumptive ...
Kaleido Scope

Understanding social media algorithms: 101 for parents

But the real question is: connected to what? Parker Woodroof, Ph.D., a social media expert and associate professor of marketing at the Collat School of Business at the University of Alabama at ...
C&EN

Supervised Learning Algorithm Reveals the Mechanistic Role of Extracellular Polymeric Substances in Biofouling of an Anaerobic Electrochemical Membrane Bioreactor

State Key Laboratory of Water Pollution Control and Green Resource Recycling, Key Laboratory of Yangtze River Water Environment of Ministry of Education, Shanghai Institute of Pollution Control and ...
IEEE

Multi-Modal Self-Supervised Learning Algorithm-Based Product Recommendation

Abstract: With the rise of e-commerce, personalized recommendation algorithms have received much attention in recent years. Meanwhile, multimodal recommendation algorithms have become the next ...
List of Banks in Belarus

Supervised vs. Unsupervised AI in Finance: Where Machine Learning is Heading

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...
techxplore

Self-supervised machine learning adapts to new tasks without retraining

The field of machine learning is traditionally divided into two main categories: "supervised" and "unsupervised" learning. In supervised learning, algorithms are trained on labeled data, where each ...