3 citations · 3 across the 4 of their papers we have counts for
4 papers
a-TMFG: Scalable Triangulated Maximally Filtered Graphs via Approximate Nearest Neighbors
Lionel Yelibi
The traditional Triangular Maximally Filtered Graph (TMFG) construction requires pre-computation and storage of a dense correlation matrix; this limits its applicability to small a…
MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning
Shay Deutsch, Lionel Yelibi, Alex Tong Lin +1
Deriving meaningful representations from complex, high-dimensional data in unsupervised settings is crucial across diverse machine learning applications. This paper introduces a fr…
Agglomerative Likelihood Clustering
Lionel Yelibi, Tim Gebbie
We consider the problem of fast time-series data clustering. Building on previous work modeling the correlation-based Hamiltonian of spin variables we present an updated fast non-e…
Fast Super-Paramagnetic Clustering
Lionel Yelibi, Tim Gebbie
We map stock market interactions to spin models to recover their hierarchical structure using a simulated annealing based Super-Paramagnetic Clustering (SPC) algorithm. This is dir…