IEEE

Direct Spectral Clustering With New Graph Learning for Better Fitting

Abstract: Traditional spectral clustering methods struggle with scalability and robustness in large datasets due to their reliance on similarity matrices and EigenValue Decomposition. We introduce two ...
netinfluencer

New Platform Visible Things Targets Algorithm-Dependent Creators With Direct-To-Fan Infrastructure

TV executives Billy Cooper, Andrew Greenberger, and Willis Robertson have launched Visible Things, a technology platform designed to help talent and brands build direct, monetizable relationships with ...
marktechpost

How to Align Large Language Models with Human Preferences Using Direct Preference Optimization, QLoRA, and Ultra-Feedback

In this tutorial, we implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We combine TRL’s DPOTrainer ...
Scientific Research Publishing

Huang, Z. (1997) A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining. Data Mining and Knowledge Discovery, 3, 34-39.

ABSTRACT: This work describes a data integration model using the Statistical Matching methodology (hot deck distance) to integrate two surveys conducted by ISTAT (EU-SILC) and the Bank of Italy ...
Scientific Research Publishing

Stringer, C., Wang, T., Michaelos, M., et al. (2020) Cellpose: A Generalist Algorithm for Cellular Segmentation. Nature Methods, 18, 100-106.

ABSTRACT: Spatial transcriptomics is undergoing rapid advancements and iterations. It is a beneficial tool to significantly enhance our understanding of tissue organization and relationships between ...
GitHub

More clusters from hierarchical clustering than direct 30% CD-HIT run

I’ve observed an unexpected result when comparing direct clustering using CD-HIT at 40% threshold versus hierarchical clustering down to 30%. Direct clustering (-c 0.4): I have directly used cd-hit to ...
IEEE

Density Peaks Clustering Algorithm Based on Neighborhood Radius and Membership Degree

Abstract: The density peaks clustering (DPC) algorithm is a density-based clustering method that effectively identifies clusters with uniform densities. However, if the datasets have uneven density, ...