3 papers
cs.DS2026
Testing Sparse Functions over the Reals
Vipul Arora, Arnab Bhattacharyya, Philips George John +1
Over the last three decades, function testing has been extensively studied over Boolean, finite fields, and discrete settings. However, to encode the real-world applications more s…
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.LG2024
Distribution Learning Meets Graph Structure Sampling
Arnab Bhattacharyya, Sutanu Gayen, Philips George John +2
This work establishes a novel link between the problem of PAC-learning high-dimensional graphical models and the task of (efficient) counting and sampling of graph structures, usin…