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.

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 ...
IEEE

K-Means and Alternative Clustering Methods in Modern Power Systems

Abstract: As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data ...
www.cs.utexas.edu

Graclus software

Graclus (latest: Version 1.2) is a fast graph clustering software that computes normalized cut and ratio association for a given undirected graph without any eigenvector computation. This is possible ...
The Marshall Project

How We Cleaned Up and Clarified Federal Data on Deaths in Custody

Under the terms of the Death in Custody Reporting Act, the Justice Department is required to collect information about everyone who dies in prisons and jails across the United States. The intention ...
PNAS

Single-cell analysis via manifold fitting: A framework for RNA clustering and beyond

Contributed by Shing-Tung Yau; received January 29, 2024; accepted July 19, 2024; reviewed by Stephan Huckemann and Jingyi Jessica Li Single-cell RNA sequencing (scRNA-seq) analysis, crucial for ...
Analytics Insight

Most Important AI Algorithms for Beginners in 2025

As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with technology. For those starting their journey in AI, it’s essential to ...
Psychology Today

Brain-Computer Interfaces Boosted by Novel AI Algorithm

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...
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 ...
Visual Studio Magazine

K-Means Data Clustering from Scratch Using C#

K-means is comparatively simple and works well with large datasets, but it assumes clusters are circular/spherical in shape, so it can only find simple cluster geometries. Data clustering is the ...
GitHub

Machine Learning Methods: Clustering

Created with R2024b. Compatible with R2024b and later releases. You can use these live scripts as demonstrations in lectures, class activities, or interactive assignments outside class. This module ...