C&EN

Illuminating the Interface of Blocc Chemistry and Data Science: An Introduction to K-Nearest Neighbor Analysis and K-Medoids Clustering

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The discovery of functional small molecules, chemical matter ...
Frontiers

Density peak clustering algorithm based on weighted mutual K-nearest neighbors

1 School of Computer Science and Technology, Yibin University, Yibin, China 2 School of Computer and Software, Southwest Petroleum University, Chengdu, China Ever since Density Peak Clustering (DPC) ...
Reuters

Exclusive: TikTok prepares US app with its own algorithm and user data

NEW YORK, July 9 (Reuters) - TikTok is preparing to launch a standalone app for U.S. users that is expected to operate on a separate algorithm and data system from its global app, laying the ...
GitHub

Approximate Sparse Nearest-Neighbor Search in OpenSearch

Since version 2.11, OpenSearch has supported neural sparse retrieval as a novel semantic search approach. Leveraging inverted index technology, this method achieves efficiency comparable to ...
marktechpost

RXTX: A Machine Learning-Guided Algorithm for Efficient Structured Matrix Multiplication

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...