5 papers
Learning under Latent Group Sparsity via Diffusion on Networks
Subhroshekhar Ghosh, Soumendu Sundar Mukherjee
Group or cluster structure on explanatory variables in machine learning problems is a very general phenomenon, which has attracted broad interest from practitioners and theoreticia…
Bulk Spectra of Truncated Sample Covariance Matrices
Subhroshekhar Ghosh, Soumendu Sundar Mukherjee, Himasish Talukdar
Determinantal Point Processes (DPPs), which originate from quantum and statistical physics, are known for modelling diversity. Recent research [Ghosh and Rigollet (2020)] has demon…
Implicit Regularization via Spectral Neural Networks and Non-linear Matrix Sensing
Hong T. M. Chu, Subhro Ghosh, Chi Thanh Lam +1
The phenomenon of implicit regularization has attracted interest in recent years as a fundamental aspect of the remarkable generalizing ability of neural networks. In a nutshell, i…
Minimax-optimal estimation for sparse multi-reference alignment with collision-free signals
Subhro Ghosh, Soumendu Sundar Mukherjee, Jing Bin Pan
The Multi-Reference Alignment (MRA) problem aims at the recovery of an unknown signal from repeated observations under the latent action of a group of cyclic isometries, in the pre…
Sparse Multi-Reference Alignment : Phase Retrieval, Uniform Uncertainty Principles and the Beltway Problem
Subhro Ghosh, Philippe Rigollet
Motivated by cutting-edge applications like cryo-electron microscopy (cryo-EM), the Multi-Reference Alignment (MRA) model entails the learning of an unknown signal from repeated me…