2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.DS2024★ 1 cited
Testing vs Estimation for Index-Invariant Properties in the Huge Object Model
Sourav Chakraborty, Eldar Fischer, Arijit Ghosh +3
The Huge Object model of property testing [Goldreich and Ron, TheoretiCS 23] concerns properties of distributions supported on , where is so large that even reading…
cs.LG2024
Efficient Sample-optimal Learning of Gaussian Tree Models via Sample-optimal Testing of Gaussian Mutual Information
Sutanu Gayen, Sanket Kale, Sayantan Sen
Learning high-dimensional distributions is a significant challenge in machine learning and statistics. Classical research has mostly concentrated on asymptotic analysis of such dat…
cs.DS2022★ 2 cited
Testing of Index-Invariant Properties in the Huge Object Model
Sourav Chakraborty, Eldar Fischer, Arijit Ghosh +2
The study of distribution testing has become ubiquitous in the area of property testing, both for its theoretical appeal, as well as for its applications in other fields of Compute…