Fuzheng Liu Examines Transformer-XL Modeling of E-Commerce User Behavior and Real-Time Behavioral Analysis

XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Optimizing RNA design with AI and an Ising machine: Encoding matters

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
BMJ Open

Implementation determinants of a planned machine learning-enabled surgical scheduling system in a high-volume orthopaedic centre in Canada: qualitative findin…

Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...

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 ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
Frontiers

A graph clustering algorithm with hypergraph learning and a core-attachment strategy for protein complex identification

Protein complexes play a crucial role in cellular biological processes. Identifying these complexes is essential for understanding cellular functions and biological mechanisms. Graph clustering ...
Frontiers

Uncovering distinct clinical phenotypes in disseminated intravascular coagulation through machine learning-enabled cluster analysis

Disseminated intravascular coagulation (DIC) is a critical condition encountered in the intensive care unit (ICU), characterized by multiple etiologies and variable outcomes. Distinguishing between ...
IEEE

Clustering Routing Protocol in WSNs Using a Hybrid of Swarm Intelligence Algorithms and Machine Learning

Abstract: Wireless Sensor Networks (WSNs) deployed in wilderness for natural disaster prevention face challenges due to the limited energy of sensor nodes, which restricts network performance and ...