1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
StiefelGen: A Simple, Model Agnostic Approach for Time Series Data Augmentation over Riemannian Manifolds
Prasad Cheema, Mahito Sugiyama
Data augmentation is an area of research which has seen active development in many machine learning fields, such as in image-based learning models, reinforcement learning for self…
stat.ML2020★ 1 cited
Double Descent Risk and Volume Saturation Effects: A Geometric Perspective
Prasad Cheema, Mahito Sugiyama
The appearance of the double-descent risk phenomenon has received growing interest in the machine learning and statistics community, as it challenges well-understood notions behind…