How to Read the Market’s Footprints Before the Crowd Does Zcash just bounced strongly off the $300 support. The daily RSI is ...

IO-aware batched K-Means for Apple Silicon, ported from Flash-KMeans (Triton/CUDA) to pure MLX. 500K points, 128 dimensions, K=1000 clustered in 0.76s on M3 Ultra -- 160x faster than sklearn. Uses ...

Abstract: We propose the weighted K-harmonic means (WKHM) clustering algorithm, a regularized variant of Kharmonic means designed to ensure numerical stability while enabling soft assignments through ...

Abstract: In $k$-means clustering, the selection of initial seeds significantly influences the quality of the resulting clusters. Moreover, clustering large-sized ...

The implementation of our paper 't-k-means: A Robust and Stable k-means Variant', accepted by the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021. This project ...

Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...

The Cleveland Guardians' successful pitching development group isn't a secret. They have a strong history of turning prospects into aces with long, successful careers. However, the Guardians are ...