4 citations · 9 across the 18 of their papers we have counts for
6 papers · 1 filter
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…
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…
Learning Networks from Gaussian Graphical Models and Gaussian Free Fields
Subhro Ghosh, Soumendu Sundar Mukherjee, Hoang-Son Tran +1
We investigate the problem of estimating the structure of a weighted network from repeated measurements of a Gaussian Graphical Model (GGM) on the network. In this vein, we conside…
Consistent model selection in the spiked Wigner model via AIC-type criteria
Soumendu Sundar Mukherjee
Consider the spiked Wigner model \[ X = \sum_{i = 1}^k λ_i u_i u_i^\top + σG, \] where is an GOE random matrix, and the eigenvalues are all spiked, i.e. abov…
High dimensional PCA: a new model selection criterion
Abhinav Chakraborty, Soumendu Sundar Mukherjee, Arijit Chakrabarti
Given a random sample from a multivariate population, estimating the number of large eigenvalues of the population covariance matrix is an important problem in Statistics with wide…
When random initializations help: a study of variational inference for community detection
Purnamrita Sarkar, Y. X. Rachel Wang, Soumendu Sundar Mukherjee
Variational approximation has been widely used in large-scale Bayesian inference recently, the simplest kind of which involves imposing a mean field assumption to approximate compl…