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, ...

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 ...
BMJ Global Health

Clustering of countries based on national essential medicines lists: cross-sectional study

Introduction National essential medicines lists (NEMLs) guide medicine selection and procurement and are key tools for ...
IEEE

Robust k-Means-Type Clustering for Noisy Data

Abstract: Data clustering is a fundamental machine learning task that seeks to categorize a dataset into homogeneous groups. However, real data usually contain noise, which poses significant ...
eLife

Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys

The subthalamic nucleus contains subpopulations with different contributions to deliberative decision-making based on noisy evidence and reward-driven preferences.
IEEE

A possibilistic fuzzy c-means clustering algorithm

Abstract: In 1997, we proposed the fuzzy-possibilistic c-means (FPCM) model and algorithm that generated both membership and typicality values when clustering unlabeled data. FPCM constrains the ...
Nature

What is the expectation maximization algorithm?

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...