3 papers
stat.AP2020
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data
Sergey E. Golovenkin, Jonathan Bac, Alexander Chervov +5
Large observational clinical datasets become increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considere…
cs.LG2020
Local intrinsic dimensionality estimators based on concentration of measure
Jonathan Bac, Andrei Zinovyev
Intrinsic dimensionality (ID) is one of the most fundamental characteristics of multi-dimensional data point clouds. Knowing ID is crucial to choose the appropriate machine learnin…
cs.LG2019
Estimating the effective dimension of large biological datasets using Fisher separability analysis
Luca Albergante, Jonathan Bac, Andrei Zinovyev
Modern large-scale datasets are frequently said to be high-dimensional. However, their data point clouds frequently possess structures, significantly decreasing their intrinsic dim…